How to exploit data on Pangeo#
Pangeo Workshop - Snow and Cloud Cover#
converted from EO-College/cubes-and-clouds
original author: Michele Clous @clausmichele conversion by: Pangeo volunteers (Pier Lorenzo Marasco @pl-marasco, Alejandro Coca-Castro @acocac, Anne Fouilloux @annefou, Justus Magin @keewis, Tina Odaka @tinaodaka)
Introduction#
In this exercise, we will build a complete the same EO workflow as OpenEO using cloud provided data (STAC Catalogue), processing it locally; from data access to obtaining the result.
We are going to follow these steps in our analysis:
Load satellite collections
Specify the spatial, temporal extents and the features we are interested in
Process the satellite data to retrieve snow cover information
aggregate information in data cubes
Visualize and analyse the results
#
Important Infos
More information on Pangeo can be found here: https://pangeo.io/ More information on the STAC specification can be found here: https://stacspec.org/
Import libraries#
# Data Manipulation and Analysis Libraries
import pandas as pd
import numpy as np
# Geospatial Data Handling Libraries
import geopandas as gpd
from shapely.geometry import mapping
import pyproj
# Multidimensional and Satellite Data Libraries
import xarray as xr
import rioxarray as rio
import stackstac
# Data Visualization Libraries
import holoviews as hv
import hvplot.xarray
import hvplot.pandas
# Data parallelization and distributed computing libraries
import dask
from dask.distributed import Client, progress, LocalCluster
# STAC Catalogue Libraries
import pystac_client
Here we creates a Dask client, which is essential for managing and executing parallel computations efficiently in the subsequent parts of the notebook. There are situation where you can connect to a Dask Gateway, but for this exercise we will use a local cluster.
cluster = LocalCluster()
client = Client(cluster)
Client address can be copy and pasted to the dashboard to monitor the progress of the computations.
client
Client
Client-d52f8761-7811-11ee-8f16-000d3a5a6945
| Connection method: Cluster object | Cluster type: distributed.LocalCluster |
| Dashboard: http://127.0.0.1:8787/status |
Cluster Info
LocalCluster
d605c996
| Dashboard: http://127.0.0.1:8787/status | Workers: 2 |
| Total threads: 2 | Total memory: 6.76 GiB |
| Status: running | Using processes: True |
Scheduler Info
Scheduler
Scheduler-c1f9fe34-a205-4821-9de0-83ee918f2680
| Comm: tcp://127.0.0.1:39049 | Workers: 2 |
| Dashboard: http://127.0.0.1:8787/status | Total threads: 2 |
| Started: Just now | Total memory: 6.76 GiB |
Workers
Worker: 0
| Comm: tcp://127.0.0.1:44847 | Total threads: 1 |
| Dashboard: http://127.0.0.1:36559/status | Memory: 3.38 GiB |
| Nanny: tcp://127.0.0.1:46087 | |
| Local directory: /tmp/dask-scratch-space/worker-b2scfmyk | |
Worker: 1
| Comm: tcp://127.0.0.1:41697 | Total threads: 1 |
| Dashboard: http://127.0.0.1:37359/status | Memory: 3.38 GiB |
| Nanny: tcp://127.0.0.1:34579 | |
| Local directory: /tmp/dask-scratch-space/worker-ogy4ppl9 | |
We will use the catchment as our area of interest (AOI) for the analysis. The catchment is defined by a polygon, which we will load from a GeoJSON file. The GeoJSON file contains the geometry of the catchment in the WGS84 coordinate reference system (EPSG:4326) and that has to be defined.
aoi = gpd.read_file('../data/catchment_outline.geojson', crs="EPGS:4326")
aoi_geojson = mapping(aoi.iloc[0].geometry)
Load satellite collections#
We will utilize the STAC API to search for satellite data in this exercise, specifically leveraging the API provided by AWS/Element84. The STAC API operates as a RESTful service, enabling the querying of satellite data with various filters such as spatial range, time period, and other specific metadata. This API is constructed based on the STAC specification, a collaborative, community-driven standard aimed at enhancing the discoverability and usability of satellite data. Numerous data providers, including AWS, Google Earth Engine, and Planet (Copernicus Data Space Ecosystem (CDSE) is coming soon **), among others, have implemented the STAC API, exemplifying its widespread adoption and utility in accessing diverse satellite datasets. We will limit the serch to the Sentinel 2 L2A collection, which is a collection of Sentinel 2 data that has been processed to surface reflectance (Top Of Canopy). We will also limit the search to the time period between 1st February 2019 and 10th June 2019 and to the extent of the catchment. ** at the moment of writing the STAC catalog of the CDSE is not yet fully operational.
URL = "https://earth-search.aws.element84.com/v1"
catalog = pystac_client.Client.open(URL)
items = catalog.search(
intersects=aoi_geojson,
collections=["sentinel-2-l2a"],
datetime="2019-02-01/2019-06-10"
).item_collection()
len(items)
101
Get bands information#
As the original data provides bands with different names than the original Sentinel 2 bands, we need to get the information about the bands.
# Get bands information
# selected_item = items[1]
# for key, asset in selected_item.assets.items():
# print(f"{key}: {asset.title}")
Load data#
We will use the stackstac library to load the data. The stackstac library is a library that allows loading data from a STAC API into an xarray dataset. Here we will load the green and swir16 bands, which are the bands we will use to calculate the snow cover. We will also load the scl band, which is the scene classification layer, which we will use to mask out clouds. Spatial resolution of 20m is selected for the analysis. The data is loaded in chunks of 2048x2048 pixels, about this we will talk more later.
ds = stackstac.stack(items,
bounds_latlon=aoi.iloc[0].geometry.bounds,
resolution=20,
chunksize=2048,
assets=['green', 'swir16', 'scl'])
/home/runner/micromamba/envs/bids23/lib/python3.11/site-packages/stackstac/prepare.py:408: UserWarning: The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.
times = pd.to_datetime(
Calculate snow cover#
We will calculate the Normalized Difference Snow Index (NDSI) to calculate the snow cover. The NDSI is calculated as the difference between the green and the swir16 bands divided by the sum of the green and the swir16 bands. For a metter of clarity we will define the green and the swir16 bands as variables. Other approches can be used to manage the data, but this is the one we will use in this exercise.
green = ds.sel(band='green')
swir = ds.sel(band='swir16')
scl = ds.sel(band='scl')
We will calculate the NDSI and we will mask out the clouds. We will use the scene classification layer (scl) to mask out the clouds. The scl is a layer that contains information about the type of land cover. We will mask out the clouds, which are identified by the values 8 and 9 in the scl layer.
ndsi = (green - swir) / (green + swir)
Dask allow to persist the data in memory, which is useful to speed up the computation. The persist method will load the data in memory and will keep it there until the end of the analysis. More explanation about persist, load and other dask related topics will be given in the next part of the exercise.
ndsi = ndsi.persist()
We will mask out the clouds, which are identified by the values 8 and 9 in the scl layer. More dettailed info can be found here: https://sentinel.esa.int/web/sentinel/technical-guides/sentinel-2-msi/level-2a/algorithm-overview
snow = xr.where((ndsi > 0.42) & ~np.isnan(ndsi), 1, ndsi)
snowmap = xr.where((snow <= 0.42) & ~np.isnan(snow), 0, snow)
# mask = (scl != 8) & (scl != 9) & (scl != 3)
mask = np.logical_not(scl.isin([8, 9, 3])) # more elegant but not sure about it from a teaching perspective
snow_cloud = xr.where(mask, snowmap, 2)
Mask data#
As we are only interestd to the snow cover in the catchment, we will mask out the data outside the catchment. To acheive it we need to convert the catchment geometry to the same coordinate reference system as the data. The data is in the UTM32N coordinate reference system (EPSG:32632).
aoi_utm32 = aoi.to_crs(epsg=32632)
geom_utm32 = aoi_utm32.iloc[0]['geometry']
As we are going to use the RioXarray library to mask out the data, we need to add some more information to the data. We need to specify the coordinate reference system and the nodata value. Both informations can be found in the metadata of the data but we need to reinforce it so that RioXarray can use it.
snow_cloud.rio.write_crs("EPSG:32632", inplace=True)
snow_cloud.rio.set_nodata(np.nan, inplace=True)
<xarray.DataArray 'stackstac-52669bdd70ae76273b7d9b61505a51e7' (time: 101,
y: 1708, x: 1367)>
dask.array<where, shape=(101, 1708, 1367), dtype=float64, chunksize=(1, 1708, 1367), chunktype=numpy.ndarray>
Coordinates: (12/53)
* time (time) datetime64[ns] 2019-02-01...
id (time) <U24 'S2B_32TPT_20190201_...
band <U6 'scl'
* x (x) float64 6.538e+05 ... 6.811e+05
* y (y) float64 5.203e+06 ... 5.169e+06
s2:generation_time (time) <U27 '2019-02-01T12:56:55...
... ...
title <U30 'Scene classification map (...
common_name object None
center_wavelength object None
full_width_half_max object None
epsg int64 32632
spatial_ref int64 0- time: 101
- y: 1708
- x: 1367
- dask.array<chunksize=(1, 1708, 1367), meta=np.ndarray>
Array Chunk Bytes 1.76 GiB 17.81 MiB Shape (101, 1708, 1367) (1, 1708, 1367) Dask graph 101 chunks in 21 graph layers Data type float64 numpy.ndarray - time(time)datetime64[ns]2019-02-01T10:27:41.665000 ... 2...
array(['2019-02-01T10:27:41.665000000', '2019-02-01T10:27:55.803000000', '2019-02-03T10:17:41.721000000', '2019-02-03T10:17:56.196000000', '2019-02-06T10:27:38.251000000', '2019-02-06T10:27:52.378000000', '2019-02-08T10:17:45.015000000', '2019-02-08T10:17:59.486000000', '2019-02-11T10:27:41.425000000', '2019-02-11T10:27:55.562000000', '2019-02-13T10:17:41.410000000', '2019-02-13T10:17:55.888000000', '2019-02-16T10:27:37.782000000', '2019-02-16T10:27:51.906000000', '2019-02-18T10:17:44.392000000', '2019-02-18T10:17:58.867000000', '2019-02-21T10:38:42.647000000', '2019-02-21T10:41:10.812000000', '2019-02-23T10:19:13.347000000', '2019-02-26T10:41:01.433000000', '2019-02-26T10:41:55.303000000', '2019-02-28T10:21:35.588000000', '2019-02-28T10:29:49.805000000', '2019-03-03T10:33:41.307000000', '2019-03-03T10:36:05.204000000', '2019-03-05T10:22:31.946000000', '2019-03-05T10:30:35.058000000', '2019-03-08T10:42:08.379000000', '2019-03-08T10:42:27.451000000', '2019-03-10T10:17:56.798000000', '2019-03-10T10:28:22.527000000', '2019-03-13T10:36:46.652000000', '2019-03-13T10:39:12.927000000', '2019-03-15T10:20:59.295000000', '2019-03-15T10:29:06.351000000', '2019-03-18T10:37:10.029000000', '2019-03-18T10:39:22.262000000', '2019-03-20T10:19:22.499000000', '2019-03-20T10:27:32.752000000', '2019-03-23T10:36:21.527000000', '2019-03-23T10:38:46.412000000', '2019-03-25T10:20:53.406000000', '2019-03-25T10:29:20.163000000', '2019-03-28T10:35:16.487000000', '2019-03-28T10:35:16.629000000', '2019-03-28T10:40:53.056000000', '2019-03-28T10:42:15.585000000', '2019-03-30T10:22:02.335000000', '2019-03-30T10:30:34.915000000', '2019-04-02T10:27:48.466000000', '2019-04-02T10:30:54.718000000', '2019-04-04T10:18:06.913000000', '2019-04-04T10:26:41.592000000', '2019-04-07T10:38:10.473000000', '2019-04-07T10:40:29.076000000', '2019-04-09T10:25:25.369000000', '2019-04-09T10:33:58.503000000', '2019-04-12T10:30:15.981000000', '2019-04-12T10:32:48.834000000', '2019-04-14T10:17:55.475000000', '2019-04-14T10:27:14.986000000', '2019-04-17T10:27:52.483000000', '2019-04-17T10:30:14.193000000', '2019-04-19T10:24:00.526000000', '2019-04-19T10:32:34.802000000', '2019-04-22T10:28:35.634000000', '2019-04-22T10:42:36.803000000', '2019-04-24T10:19:36.413000000', '2019-04-24T10:27:43.597000000', '2019-04-27T10:27:44.859000000', '2019-04-27T10:27:58.984000000', '2019-04-29T10:17:52.241000000', '2019-04-29T10:18:06.712000000', '2019-05-02T10:27:49.108000000', '2019-05-02T10:28:03.252000000', '2019-05-04T10:17:48.626000000', '2019-05-04T10:18:03.103000000', '2019-05-07T10:27:45.232000000', '2019-05-07T10:27:59.373000000', '2019-05-09T10:17:53.127000000', '2019-05-09T10:18:07.599000000', '2019-05-12T10:27:49.818000000', '2019-05-12T10:28:03.963000000', '2019-05-14T10:17:48.610000000', '2019-05-14T10:18:03.075000000', '2019-05-17T10:27:45.056000000', '2019-05-17T10:27:59.182000000', '2019-05-19T10:17:53.452000000', '2019-05-19T10:18:07.921000000', '2019-05-24T10:17:48.052000000', '2019-05-24T10:18:02.521000000', '2019-05-27T10:27:44.339000000', '2019-05-27T10:27:58.464000000', '2019-05-29T10:17:53.232000000', '2019-05-29T10:18:07.701000000', '2019-06-01T10:27:49.632000000', '2019-06-01T10:28:03.768000000', '2019-06-03T10:17:47.026000000', '2019-06-03T10:18:01.498000000', '2019-06-06T10:27:43.405000000', '2019-06-06T10:27:57.521000000'], dtype='datetime64[ns]') - id(time)<U24'S2B_32TPT_20190201_0_L2A' ... '...
array(['S2B_32TPT_20190201_0_L2A', 'S2B_32TPS_20190201_0_L2A', 'S2A_32TPT_20190203_0_L2A', 'S2A_32TPS_20190203_0_L2A', 'S2A_32TPT_20190206_0_L2A', 'S2A_32TPS_20190206_0_L2A', 'S2B_32TPT_20190208_0_L2A', 'S2B_32TPS_20190208_0_L2A', 'S2B_32TPT_20190211_0_L2A', 'S2B_32TPS_20190211_0_L2A', 'S2A_32TPT_20190213_0_L2A', 'S2A_32TPS_20190213_0_L2A', 'S2A_32TPT_20190216_0_L2A', 'S2A_32TPS_20190216_0_L2A', 'S2B_32TPT_20190218_0_L2A', 'S2B_32TPS_20190218_0_L2A', 'S2B_32TPT_20190221_0_L2A', 'S2B_32TPS_20190221_0_L2A', 'S2A_32TPS_20190223_0_L2A', 'S2A_32TPT_20190226_0_L2A', 'S2A_32TPS_20190226_0_L2A', 'S2B_32TPT_20190228_0_L2A', 'S2B_32TPS_20190228_0_L2A', 'S2B_32TPT_20190303_0_L2A', 'S2B_32TPS_20190303_0_L2A', 'S2A_32TPT_20190305_0_L2A', 'S2A_32TPS_20190305_0_L2A', 'S2A_32TPS_20190308_1_L2A', 'S2A_32TPT_20190308_1_L2A', 'S2B_32TPT_20190310_0_L2A', 'S2B_32TPS_20190310_0_L2A', 'S2B_32TPT_20190313_0_L2A', 'S2B_32TPS_20190313_0_L2A', 'S2A_32TPT_20190315_0_L2A', 'S2A_32TPS_20190315_0_L2A', 'S2A_32TPT_20190318_0_L2A', 'S2A_32TPS_20190318_0_L2A', 'S2B_32TPT_20190320_0_L2A', 'S2B_32TPS_20190320_0_L2A', 'S2B_32TPT_20190323_0_L2A', ... 'S2A_32TPS_20190417_0_L2A', 'S2B_32TPS_20190419_0_L2A', 'S2B_32TPT_20190419_0_L2A', 'S2B_32TPS_20190422_0_L2A', 'S2B_32TPT_20190422_0_L2A', 'S2A_32TPT_20190424_0_L2A', 'S2A_32TPS_20190424_0_L2A', 'S2A_32TPT_20190427_0_L2A', 'S2A_32TPS_20190427_0_L2A', 'S2B_32TPT_20190429_0_L2A', 'S2B_32TPS_20190429_0_L2A', 'S2B_32TPT_20190502_0_L2A', 'S2B_32TPS_20190502_0_L2A', 'S2A_32TPT_20190504_0_L2A', 'S2A_32TPS_20190504_0_L2A', 'S2A_32TPT_20190507_0_L2A', 'S2A_32TPS_20190507_0_L2A', 'S2B_32TPT_20190509_0_L2A', 'S2B_32TPS_20190509_0_L2A', 'S2B_32TPT_20190512_0_L2A', 'S2B_32TPS_20190512_0_L2A', 'S2A_32TPT_20190514_0_L2A', 'S2A_32TPS_20190514_0_L2A', 'S2A_32TPT_20190517_0_L2A', 'S2A_32TPS_20190517_0_L2A', 'S2B_32TPT_20190519_0_L2A', 'S2B_32TPS_20190519_0_L2A', 'S2A_32TPT_20190524_0_L2A', 'S2A_32TPS_20190524_0_L2A', 'S2A_32TPT_20190527_0_L2A', 'S2A_32TPS_20190527_0_L2A', 'S2B_32TPT_20190529_0_L2A', 'S2B_32TPS_20190529_0_L2A', 'S2B_32TPT_20190601_0_L2A', 'S2B_32TPS_20190601_0_L2A', 'S2A_32TPT_20190603_0_L2A', 'S2A_32TPS_20190603_0_L2A', 'S2A_32TPT_20190606_0_L2A', 'S2A_32TPS_20190606_0_L2A'], dtype='<U24') - band()<U6'scl'
array('scl', dtype='<U6') - x(x)float646.538e+05 6.538e+05 ... 6.811e+05
array([653760., 653780., 653800., ..., 681040., 681060., 681080.])
- y(y)float645.203e+06 5.203e+06 ... 5.169e+06
array([5202800., 5202780., 5202760., ..., 5168700., 5168680., 5168660.])
- s2:generation_time(time)<U27'2019-02-01T12:56:55.000000Z' .....
array(['2019-02-01T12:56:55.000000Z', '2019-02-01T12:56:55.000000Z', '2019-02-03T12:44:25.000000Z', '2019-02-03T12:44:25.000000Z', '2019-02-06T13:20:04.000000Z', '2019-02-06T13:20:04.000000Z', '2019-02-08T13:21:21.000000Z', '2019-02-08T13:21:21.000000Z', '2019-02-11T14:36:27.000000Z', '2019-02-11T14:36:27.000000Z', '2019-02-13T16:22:53.000000Z', '2019-02-13T16:22:53.000000Z', '2019-02-16T13:04:28.000000Z', '2019-02-16T13:04:28.000000Z', '2019-02-18T16:16:20.000000Z', '2019-02-18T16:16:20.000000Z', '2019-02-21T16:24:47.000000Z', '2019-02-21T16:24:47.000000Z', '2019-02-23T13:45:48.000000Z', '2019-02-26T14:34:34.000000Z', '2019-02-26T14:34:34.000000Z', '2019-02-28T14:30:58.000000Z', '2019-02-28T14:30:58.000000Z', '2019-03-03T18:09:04.000000Z', '2019-03-03T18:09:04.000000Z', '2019-03-05T16:28:51.000000Z', '2019-03-05T16:28:51.000000Z', '2019-03-08T16:29:20.000000Z', '2019-03-08T16:29:20.000000Z', '2019-03-10T17:58:32.000000Z', '2019-03-10T17:58:32.000000Z', '2019-03-13T16:30:42.000000Z', '2019-03-13T16:30:42.000000Z', '2019-03-15T13:28:29.000000Z', '2019-03-15T13:28:29.000000Z', '2019-03-18T16:32:57.000000Z', '2019-03-18T16:32:57.000000Z', '2019-03-20T19:51:48.000000Z', '2019-03-20T19:51:48.000000Z', '2019-03-23T14:49:59.000000Z', ... '2019-04-17T13:09:13.000000Z', '2019-04-19T13:23:22.000000Z', '2019-04-19T13:23:22.000000Z', '2019-04-22T13:36:43.000000Z', '2019-04-22T13:36:43.000000Z', '2019-04-24T16:23:25.000000Z', '2019-04-24T16:23:25.000000Z', '2019-04-27T13:11:26.000000Z', '2019-04-27T13:11:26.000000Z', '2019-04-29T13:29:00.000000Z', '2019-04-29T13:29:00.000000Z', '2019-05-02T13:41:10.000000Z', '2019-05-02T13:41:10.000000Z', '2019-05-04T13:48:00.000000Z', '2019-05-04T13:48:00.000000Z', '2019-05-07T13:44:05.000000Z', '2019-05-07T13:44:05.000000Z', '2019-05-09T13:21:53.000000Z', '2019-05-09T13:21:53.000000Z', '2019-05-12T13:41:03.000000Z', '2019-05-12T13:41:03.000000Z', '2019-05-14T13:46:57.000000Z', '2019-05-14T13:46:57.000000Z', '2019-05-17T13:12:16.000000Z', '2019-05-17T13:12:16.000000Z', '2019-05-19T13:20:53.000000Z', '2019-05-19T13:20:53.000000Z', '2019-05-24T13:03:04.000000Z', '2019-05-24T13:03:04.000000Z', '2019-05-27T14:51:56.000000Z', '2019-05-27T14:51:56.000000Z', '2019-05-29T14:39:58.000000Z', '2019-05-29T14:39:58.000000Z', '2019-06-01T13:50:40.000000Z', '2019-06-01T13:50:40.000000Z', '2019-06-03T13:03:27.000000Z', '2019-06-03T13:03:27.000000Z', '2019-06-06T13:44:50.000000Z', '2019-06-06T13:44:50.000000Z'], dtype='<U27') - eo:cloud_cover(time)object94.135713 96.279123 ... 85.698733
array([94.135713, 96.279123, 99.903584, 87.69484, 40.147972, 17.612226, 24.783327, 24.117596, 97.965127, 82.441129, 3.430043, 41.138558, 14.107829, 35.529186, 9.322419, 4.520082, 2.149853, 1.078002, 4.77241, 20.066867, 75.289728, 1.251102, 1.534389, 34.215152, 11.871402, 15.342501, 6.313679, 27.36025, 33.556974, 99.808842, 44.61342, 79.539457, 77.636764, 99.999994, 55.049791, 71.115688, 64.070385, 26.716213, 26.606328, 1.29806, 2.158201, 17.990307, 78.624527, 7.296045, 18.215826, 36.546995, 27.297996, 7.765829, 6.118402, 29.300942, 74.419291, 99.675903, 64.853644, 21.062216, 66.010646, 82.949406, 87.429502, 91.590097, 50.58697, 91.510172, 93.276263, 48.470894, 21.818134, 25.100749, 5.763763, 38.186185, 44.647646, 81.029626, 95.716827, 59.497566, 27.968077, 77.708937, 86.404898, 15.548038, 13.582733, 81.32433, 81.654141, 50.578071, 83.819967, 80.087905, 50.617034, 83.485009, 99.352152, 90.224016, 23.302598, 65.623319, 98.788935, 68.312564, 86.31006, 7.424432, 9.94969, 100, 99.993604, 81.525372, 75.322388, 7.746625, 2.923318, 7.150319, 8.296014, 94.895761, 85.698733], dtype=object) - updated(time)<U24'2022-11-08T12:14:57.099Z' ... '...
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array(['MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS'], dtype='<U10') - s2:unclassified_percentage(time)object0.011951 5.6e-05 ... 2.768176
array([0.011951, 5.6e-05, 0, 0.004409, 2.61864, 5.640598, 4.763902, 4.89477, 0.000737, 1.06698, 6.379969, 3.581112, 3.75781, 4.503651, 3.415961, 5.543773, 6.000673, 6.204186, 5.974628, 4.41536, 1.325105, 4.979029, 5.612632, 4.590277, 6.777608, 6.167155, 6.077614, 6.867857, 2.550018, 0.020529, 6.43759, 2.276966, 2.925147, 0, 3.508973, 2.016566, 3.365213, 5.948313, 5.286334, 3.903815, 4.453562, 5.392561, 0.663991, 4.577908, 3.842456, 2.561705, 5.091375, 5.002561, 4.391824, 5.487678, 3.727499, 0.000222, 3.55055, 6.093498, 5.667936, 0.889327, 0.880247, 0.800342, 5.338126, 0.386644, 0.204943, 4.824572, 4.264689, 3.692116, 4.032218, 8.155444, 6.945007, 0.66158, 0.617971, 3.951247, 4.494771, 0.008768, 1.226688, 4.524324, 4.265018, 2.941594, 1.672861, 3.151683, 1.427331, 1.791112, 4.994049, 0, 7.1e-05, 1.250102, 3.509952, 2.313757, 0.087243, 3.433142, 0.07484, 4.014421, 3.469744, 0, 0, 0.00459, 0.014751, 4.330208, 3.50396, 3.27118, 2.913887, 0.843723, 2.768176], dtype=object) - s2:product_uri(time)<U65'S2B_MSIL2A_20190201T102249_N021...
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array({'sentinel2-to-stac': '0.1.0'}, dtype=object) - platform(time)<U11'sentinel-2b' ... 'sentinel-2a'
array(['sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a'], dtype='<U11') - mgrs:grid_square(time)<U2'PT' 'PS' 'PT' ... 'PS' 'PT' 'PS'
array(['PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PS', 'PT', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PS', 'PT', 'PS', 'PS', 'PT', 'PT', 'PS', 'PT', 'PT', 'PS', 'PS', 'PT', 'PT', 'PS', 'PS', 'PT', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PS', 'PT', 'PS', 'PT', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS'], dtype='<U2') - earthsearch:payload_id(time)<U74'roda-sentinel2/workflow-sentine...
array(['roda-sentinel2/workflow-sentinel2-to-stac/27d818188ce5e85723443ae3ce9f0ec6', 'roda-sentinel2/workflow-sentinel2-to-stac/c7756e556cb03e427209ed59e170bbac', 'roda-sentinel2/workflow-sentinel2-to-stac/6f2157ad2b6798a3d2230af8bd6797ed', 'roda-sentinel2/workflow-sentinel2-to-stac/6a5d17fe220672054478b92f4108c7d9', 'roda-sentinel2/workflow-sentinel2-to-stac/7826aa614df00fbdb372d086b7a7d36c', 'roda-sentinel2/workflow-sentinel2-to-stac/92de56004acdcdd7934c8928cd391cdb', 'roda-sentinel2/workflow-sentinel2-to-stac/9ddf64d74781ce6eac34b1730be320b3', 'roda-sentinel2/workflow-sentinel2-to-stac/5a36ed3a8cf7d067f920b6891b6b70a7', 'roda-sentinel2/workflow-sentinel2-to-stac/4b16e54553d664864a037c49e3e5a3e4', 'roda-sentinel2/workflow-sentinel2-to-stac/643e7785c6fb206e8543216defbaeccd', 'roda-sentinel2/workflow-sentinel2-to-stac/d35f2c7cd794327bd2818fe59c1d0c76', 'roda-sentinel2/workflow-sentinel2-to-stac/aa9a7f78e508d756ed7e8c0a6a61c83f', 'roda-sentinel2/workflow-sentinel2-to-stac/2b8f15de1746ef715d7e077bd9862f6d', 'roda-sentinel2/workflow-sentinel2-to-stac/ba6f3eb9b391095616caef44af5311aa', 'roda-sentinel2/workflow-sentinel2-to-stac/d2971a23a81d5bebae06d2528f2e368e', 'roda-sentinel2/workflow-sentinel2-to-stac/72817018462c5d402beb0343134e585f', 'roda-sentinel2/workflow-sentinel2-to-stac/9b6fde685989ca90bc038419365794c6', 'roda-sentinel2/workflow-sentinel2-to-stac/271b82f8b21483572572340e4bc82e1c', 'roda-sentinel2/workflow-sentinel2-to-stac/d4ee83c1f4cead0ebccf604ac4360205', 'roda-sentinel2/workflow-sentinel2-to-stac/12cea93e0f4bd396fdeb01f2a6f67c87', ... 'roda-sentinel2/workflow-sentinel2-to-stac/c1f054678e1bdce81f354a3a4dd1bce8', 'roda-sentinel2/workflow-sentinel2-to-stac/037578cb265b085965afb824933f3b2c', 'roda-sentinel2/workflow-sentinel2-to-stac/f62aad148421740c02b7680debcf8949', 'roda-sentinel2/workflow-sentinel2-to-stac/3f207fbdf51bacac46e150f212009f2f', 'roda-sentinel2/workflow-sentinel2-to-stac/f00409b96f3eba6f2cfd95125bd3caa1', 'roda-sentinel2/workflow-sentinel2-to-stac/638efb6bd79a1e2c09adf93999760474', 'roda-sentinel2/workflow-sentinel2-to-stac/bbdfc519ad83e508472850f049031f6e', 'roda-sentinel2/workflow-sentinel2-to-stac/8b73a814225ff2dee40f49029932ed2e', 'roda-sentinel2/workflow-sentinel2-to-stac/23b0df7fdadb8d2f1b22d28e1dc7c31c', 'roda-sentinel2/workflow-sentinel2-to-stac/eb058402470acd9b2a2fea3b23236265', 'roda-sentinel2/workflow-sentinel2-to-stac/80dc1fc54946785e70f1f1edc04e33bc', 'roda-sentinel2/workflow-sentinel2-to-stac/a88c46e47e5aebedb99141db3f23345c', 'roda-sentinel2/workflow-sentinel2-to-stac/eaca43368bb48aa6df33d93d80d163bb', 'roda-sentinel2/workflow-sentinel2-to-stac/6ccb82b7b079cc78d5f0942c37ffd957', 'roda-sentinel2/workflow-sentinel2-to-stac/363fd02cca77098ad2211c0fab1ec86a', 'roda-sentinel2/workflow-sentinel2-to-stac/0c64cb510aee8db820ff9a4b0d990319', 'roda-sentinel2/workflow-sentinel2-to-stac/32e00e2b7cc5dba7ed9325bd2bf4eea7', 'roda-sentinel2/workflow-sentinel2-to-stac/5800db9cadefa73a1365d612622c60ec', 'roda-sentinel2/workflow-sentinel2-to-stac/fdb25b0f5b5531b5065244d5331b8f43'], dtype='<U74') - earthsearch:boa_offset_applied()boolFalse
array(False)
- s2:nodata_pixel_percentage(time)object0.000103 10.936822 ... 0 10.651179
array([0.000103, 10.936822, 9.035017, 0, 0.000242, 11.058175, 8.80881, 0.000508, 0.001178, 11.054406, 8.909436, 0.000445, 0.00077, 10.979612, 8.976639, 0.001121, 0.005246, 10.948487, 0.000491, 0.000909, 22.085553, 8.972917, 0.000936, 8.3e-05, 10.811792, 9.105272, 0.000382, 10.160348, 64.006782, 8.880395, 3e-06, 0.000866, 11.102382, 9.613313, 0.003882, 0, 10.357866, 9.515041, 0.001981, 0.000415, 10.554736, 0.000325, 9.277332, 14.97362, 81.199092, 91.406816, 0.268768, 0.000202, 9.107425, 9.6e-05, 10.765276, 0, 9.213974, 7.6e-05, 10.927774, 0, 8.74318, 0.002386, 11.157236, 9.013481, 0, 0.000876, 11.015444, 3.6e-05, 8.53733, 11.414159, 0.006506, 8.831852, 0, 0.001652, 11.207292, 8.347301, 0, 0.009967, 11.529136, 8.854675, 0, 0.001835, 11.179462, 8.174197, 1e-05, 0.014496, 11.674032, 8.956078, 7e-06, 0.000222, 11.040318, 8.240474, 0, 9.063792, 2e-05, 4e-05, 10.885637, 8.353151, 0, 0.007133, 11.447613, 9.397335, 0.000514, 0, 10.651179], dtype=object) - s2:high_proba_clouds_percentage(time)object28.474605 8.089755 ... 68.302697
array([28.474605, 8.089755, 0, 8.097946, 0.347863, 0.404564, 3.18249, 13.025998, 3.795855, 16.476883, 0.722417, 2.996168, 0.191315, 0.345278, 0.378075, 0.524364, 0.404088, 0.428093, 3.221123, 0.411011, 57.985854, 0.479861, 0.58567, 1.164479, 0.555689, 10.933855, 1.66515, 22.881198, 27.283058, 1.001521, 12.859948, 68.552494, 60.841697, 0, 7.293878, 35.636574, 33.464602, 4.723628, 0.727587, 0.27859, 0.293402, 15.131488, 75.048304, 0.320798, 0.283979, 5.256074, 12.557438, 0.493941, 0.414534, 5.949093, 24.334399, 8.32763, 25.453517, 14.401695, 60.160649, 34.283876, 44.987833, 88.686782, 43.836692, 87.367743, 63.687009, 23.234625, 17.33311, 16.457643, 1.604513, 9.021848, 1.382886, 38.881776, 78.495955, 51.282567, 17.579152, 35.019681, 28.828606, 6.963654, 8.859406, 74.317372, 73.920262, 2.810752, 12.166209, 72.222966, 43.735892, 0.74115, 4.254435, 82.502216, 15.15367, 46.63088, 78.458554, 45.790553, 46.282384, 4.590221, 8.36652, 16.94798, 9.10632, 29.857177, 31.819323, 5.42523, 1.85607, 5.484578, 6.884611, 59.161156, 68.302697], dtype=object) - s2:thin_cirrus_percentage(time)object2.225559 0.00928 ... 3.543517
array([2.225559, 0.00928, 0, 0.578814, 25.953317, 1.831257, 13.336582, 1.030075, 0.387741, 11.59085, 0.024961, 11.286602, 1.586686, 16.248183, 0.407614, 0.068627, 0.489496, 0.011881, 0.002253, 17.164983, 5.989625, 0.114574, 0.009983, 20.426282, 9.359232, 0.348671, 0.106944, 0.303773, 0.628434, 0.023274, 4.190633, 1.807296, 5.32212, 0, 3.040526, 1.687068, 2.680191, 1.256244, 2.433099, 0.01925, 0.00013, 0.421204, 0.662916, 0.000457, 0.000494, 0.09278, 3.227772, 2.579917, 2.847647, 6.555422, 11.507395, 0.011569, 3.647571, 2.17389, 0.141721, 1.400944, 1.107897, 1.479772, 3.255056, 0.020041, 0.150142, 10.038469, 0.895554, 0.594219, 0.097929, 5.367009, 24.042393, 8.933073, 1.100103, 2.085489, 1.311102, 0.622414, 3.660977, 4.210678, 0.969822, 0.862668, 0.18908, 15.802597, 6.322686, 0.747905, 0.120408, 0.002718, 0.000169, 1.195515, 0.775482, 3.188232, 0.098726, 5.373817, 0.078095, 1.509326, 0.103639, 0, 0, 0.522361, 1.712088, 0.420649, 0.19434, 0.367874, 0.052555, 0.241005, 3.543517], dtype=object) - view:sun_azimuth(time)float64163.9 163.8 161.1 ... 155.2 154.5
array([163.86054926, 163.77370581, 161.0959049 , 160.99036777, 163.38665794, 163.28917665, 160.62219832, 160.50454567, 162.99215074, 162.88338599, 160.16546807, 160.03450499, 162.62117436, 162.50001042, 159.78640816, 159.64117272, 162.33273248, 162.19862356, 159.26224591, 162.06176346, 161.91360695, 159.13034121, 158.95320803, 161.86499103, 161.7022021 , 158.84327907, 158.64834693, 161.49940361, 161.67789873, 158.62176727, 158.40823407, 161.55839958, 161.36362349, 158.4090363 , 158.17553626, 161.45412428, 161.242065 , 158.23655975, 157.98199941, 161.38517084, 161.15511737, 157.77852687, 158.05563993, 161.05388999, 161.05388999, 161.30338543, 161.30338543, 157.58829308, 157.88941887, 161.23672075, 160.96680719, 157.35575732, 157.68297259, 161.1261513 , 160.83388843, 157.12192929, 157.47688591, 161.01726199, 160.70134413, 157.20224767, 156.81680652, 160.83374584, 160.49155977, 156.49663989, 156.91449294, 160.26509163, 160.63521358, 156.52232228, 156.06857607, 160.3212994 , 159.91957719, 156.10029778, 155.6083854 , 159.97641954, 159.54111816, 155.543096 , 155.00901493, 159.48676354, 159.01354282, 154.95850051, 154.38032857, 158.97177509, 158.45894651, 154.23059859, 153.60472296, 158.30398116, 157.74751327, 153.50105456, 152.82739621, 152.63618058, 151.91278584, 156.81925035, 156.17298279, 151.81293831, 151.04268726, 156.05094177, 155.36170143, 150.89209112, 150.07633929, 155.18144211, 154.45002254]) - s2:datatake_id(time)<U34'GS2B_20190201T102249_009958_N02...
array(['GS2B_20190201T102249_009958_N02.11', 'GS2B_20190201T102249_009958_N02.11', 'GS2A_20190203T101221_018895_N02.11', 'GS2A_20190203T101221_018895_N02.11', 'GS2A_20190206T102211_018938_N02.11', 'GS2A_20190206T102211_018938_N02.11', 'GS2B_20190208T101159_010058_N02.11', 'GS2B_20190208T101159_010058_N02.11', 'GS2B_20190211T102149_010101_N02.11', 'GS2B_20190211T102149_010101_N02.11', 'GS2A_20190213T101131_019038_N02.11', 'GS2A_20190213T101131_019038_N02.11', 'GS2A_20190216T102111_019081_N02.11', 'GS2A_20190216T102111_019081_N02.11', 'GS2B_20190218T101059_010201_N02.11', 'GS2B_20190218T101059_010201_N02.11', 'GS2B_20190221T102039_010244_N02.11', 'GS2B_20190221T102039_010244_N02.11', 'GS2A_20190223T101021_019181_N02.11', 'GS2A_20190226T102021_019224_N02.11', ... 'GS2B_20190512T102029_011388_N02.12', 'GS2B_20190512T102029_011388_N02.12', 'GS2A_20190514T101031_020325_N02.12', 'GS2A_20190514T101031_020325_N02.12', 'GS2A_20190517T102031_020368_N02.12', 'GS2A_20190517T102031_020368_N02.12', 'GS2B_20190519T101039_011488_N02.12', 'GS2B_20190519T101039_011488_N02.12', 'GS2A_20190524T101031_020468_N02.12', 'GS2A_20190524T101031_020468_N02.12', 'GS2A_20190527T102031_020511_N02.12', 'GS2A_20190527T102031_020511_N02.12', 'GS2B_20190529T101039_011631_N02.12', 'GS2B_20190529T101039_011631_N02.12', 'GS2B_20190601T102029_011674_N02.12', 'GS2B_20190601T102029_011674_N02.12', 'GS2A_20190603T101031_020611_N02.12', 'GS2A_20190603T101031_020611_N02.12', 'GS2A_20190606T102031_020654_N02.12', 'GS2A_20190606T102031_020654_N02.12'], dtype='<U34') - earthsearch:s3_path(time)<U79's3://sentinel-cogs/sentinel-s2-...
array(['s3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2B_32TPT_20190201_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2B_32TPS_20190201_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2A_32TPT_20190203_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2A_32TPS_20190203_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2A_32TPT_20190206_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2A_32TPS_20190206_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2B_32TPT_20190208_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2B_32TPS_20190208_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2B_32TPT_20190211_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2B_32TPS_20190211_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2A_32TPT_20190213_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2A_32TPS_20190213_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2A_32TPT_20190216_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2A_32TPS_20190216_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2B_32TPT_20190218_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2B_32TPS_20190218_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2B_32TPT_20190221_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2B_32TPS_20190221_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2A_32TPS_20190223_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2A_32TPT_20190226_0_L2A', ... 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2B_32TPS_20190512_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2A_32TPT_20190514_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2A_32TPS_20190514_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2A_32TPT_20190517_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2A_32TPS_20190517_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2B_32TPT_20190519_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2B_32TPS_20190519_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2A_32TPT_20190524_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2A_32TPS_20190524_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2A_32TPT_20190527_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2A_32TPS_20190527_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2B_32TPT_20190529_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2B_32TPS_20190529_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/6/S2B_32TPT_20190601_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/6/S2B_32TPS_20190601_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/6/S2A_32TPT_20190603_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/6/S2A_32TPS_20190603_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/6/S2A_32TPT_20190606_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/6/S2A_32TPS_20190606_0_L2A'], dtype='<U79') - s2:dark_features_percentage(time)object1.308534 1.237797 ... 0.220692
array([1.308534, 1.237797, 0.034161, 0.101277, 7.692839, 20.851712, 13.294898, 15.587787, 0.077034, 1.723071, 19.534473, 12.280087, 21.493369, 19.257888, 22.405481, 20.790145, 18.783672, 20.127527, 18.078911, 12.080093, 4.725911, 17.626123, 17.116198, 5.873704, 13.002147, 10.222468, 13.593714, 8.990999, 6.079657, 0, 6.460854, 1.464981, 2.777434, 4e-06, 3.861269, 1.383761, 3.679705, 11.617623, 11.908567, 9.980234, 10.250788, 6.9092, 0.526073, 9.682282, 9.566194, 9.52535, 7.10426, 7.071975, 6.436816, 4.253971, 1.748624, 0.005153, 1.790272, 4.358801, 1.404547, 0.219084, 0.448807, 0.20305, 2.875947, 0.144373, 0.170593, 1.528588, 3.836949, 3.519545, 3.9237, 2.545508, 1.299646, 0.459325, 0.262378, 0.76153, 1.888499, 0.024142, 0.096446, 2.514954, 2.197189, 0.238995, 0.140663, 0.641695, 0.350758, 0.326455, 0.696136, 0.002008, 0.003858, 0.150131, 0.984025, 0.647242, 0.072917, 0.399238, 0.027993, 1.183329, 1.05573, 0, 0, 0, 3e-05, 1.654051, 1.453961, 1.081163, 0.874341, 0.107568, 0.220692], dtype=object) - s2:snow_ice_percentage(time)object4.407356 2.352311 ... 5.44832
array([4.407356, 2.352311, 0.05931, 12.186134, 47.520396, 43.431687, 52.38657, 43.825087, 1.947754, 14.116633, 63.632268, 37.590456, 47.635952, 26.882216, 48.269284, 41.128185, 60.625523, 43.958402, 41.597959, 54.815727, 15.990245, 52.539939, 38.421527, 45.304981, 40.83612, 45.512161, 35.859022, 37.780914, 54.080808, 0.170379, 20.941679, 8.076091, 11.862913, 0, 15.792303, 23.095481, 24.48242, 27.64447, 16.406852, 43.97696, 37.887084, 29.257828, 19.569986, 30.404931, 40.028054, 45.201612, 30.308124, 32.947722, 42.572933, 31.911319, 15.898545, 0.318708, 16.770558, 35.886163, 21.665148, 15.876842, 10.93374, 5.938221, 22.171693, 7.896252, 6.257269, 32.861185, 37.115005, 26.511607, 35.428345, 30.256045, 35.58833, 2.863022, 2.96781, 24.319336, 28.161886, 22.244364, 11.430284, 35.204297, 34.353489, 8.778142, 15.177004, 28.84759, 14.091474, 11.922268, 27.344078, 16.512518, 0.642247, 6.355498, 26.708639, 10.856315, 1.016905, 15.551555, 13.515091, 31.784019, 31.038001, 0, 0.006393, 18.458416, 24.612381, 27.292523, 30.283567, 25.201038, 25.072944, 3.380935, 5.44832], dtype=object) - s2:vegetation_percentage(time)object3.3e-05 0 0 ... 0.467271 4.627483
array([3.3e-05, 0, 0, 0, 0.129419, 3.024495, 1.335275, 3.476257, 0, 0.01874, 2.591085, 1.74686, 5.702759, 3.2968, 8.140194, 11.361623, 5.147837, 10.961309, 12.244289, 3.050694, 0.248903, 11.782508, 16.640516, 4.321283, 9.398247, 10.729123, 19.324329, 3.294571, 1.031084, 0, 8.106805, 4.785185, 1.40766, 0, 10.630693, 0.949234, 1.002168, 15.971488, 21.30038, 28.449246, 24.982615, 20.921379, 0.170554, 27.42599, 18.105584, 1.673402, 18.766998, 28.619561, 28.29192, 20.392635, 0.89143, 0, 7.852823, 20.350888, 2.709706, 0.032896, 0.085879, 1.107229, 10.944532, 0.00889, 0.031118, 8.703066, 22.132467, 27.114123, 39.840275, 16.156347, 7.824096, 13.115945, 0.312189, 7.707577, 29.86159, 0, 0.554955, 33.616117, 36.617664, 4.994705, 0.884974, 15.074661, 0.021281, 4.312731, 12.670155, 0, 0, 1.434204, 38.958597, 17.746092, 0.014001, 9.718411, 0.010922, 47.022659, 45.318523, 0, 0, 0, 0, 50.448912, 53.186417, 53.010529, 53.090888, 0.467271, 4.627483], dtype=object) - s2:medium_proba_clouds_percentage(time)float6463.44 88.18 99.9 ... 35.49 13.85
array([63.435549, 88.180089, 99.903584, 79.01808 , 13.846792, 15.376405, 8.264255, 10.061523, 93.781531, 54.373395, 2.682665, 26.855788, 12.329829, 18.935725, 8.53673 , 3.927092, 1.256269, 0.638028, 1.549034, 2.490874, 11.31425 , 0.656667, 0.938735, 12.62439 , 1.956482, 4.059975, 4.541585, 4.175279, 5.645482, 98.784047, 27.562839, 9.179667, 11.472946, 99.999994, 44.715387, 33.792046, 27.925593, 20.736341, 23.445642, 1.00022 , 1.864669, 2.437614, 2.913307, 6.97479 , 17.931353, 31.198141, 11.512786, 4.691971, 2.856221, 16.796426, 38.577497, 91.336703, 35.752556, 4.486631, 5.708276, 47.264585, 41.333771, 1.423543, 3.495222, 4.122388, 29.439113, 15.1978 , 3.58947 , 8.048888, 4.061321, 23.797327, 19.222367, 33.214778, 16.120769, 6.12951 , 9.077822, 42.066842, 53.915316, 4.373706, 3.753505, 6.14429 , 7.544799, 31.964722, 65.331072, 7.117034, 6.760735, 82.741141, 95.097548, 6.526285, 7.373446, 15.804207, 20.231655, 17.148194, 39.949581, 1.324885, 1.479531, 83.052021, 90.887284, 51.145834, 41.790977, 1.900746, 0.872907, 1.297867, 1.358848, 35.4936 , 13.852519]) - s2:degraded_msi_data_percentage()int640
array(0)
- s2:saturated_defective_pixel_percentage()int640
array(0)
- view:sun_elevation(time)float6424.07 24.94 24.11 ... 63.58 64.4
array([24.07241972, 24.94141661, 24.11166869, 24.9684836 , 25.49664938, 26.36366484, 25.57962234, 26.4341079 , 27.04993803, 27.9152628 , 27.16076928, 28.01296315, 28.70727321, 29.5709547 , 28.85348803, 29.70371374, 30.46485883, 31.32723973, 31.47808545, 32.29666219, 33.15779068, 32.48780958, 33.33453363, 34.19914284, 35.0593373 , 34.39936888, 35.24450457, 37.00534716, 36.14604869, 36.36263943, 37.20653153, 38.13331346, 38.99201242, 38.35138608, 39.19406169, 40.13740372, 40.99556917, 40.35799918, 41.19965614, 42.14830171, 43.0061052 , 43.20051401, 42.35991933, 45.00335051, 45.00335051, 44.1459899 , 44.1459899 , 45.18941908, 44.34983468, 46.12283814, 46.97983296, 47.14319961, 46.30486231, 48.05706655, 48.9134756 , 49.05721314, 48.22013551, 49.94325734, 50.79908113, 50.07054724, 50.90593871, 51.75765811, 52.61252027, 52.68747307, 51.85386678, 54.35148517, 53.49767167, 53.54317197, 54.37433061, 55.13859946, 55.99075571, 55.14060577, 55.9690822 , 56.68123536, 57.53155135, 56.61669955, 57.44159327, 58.09850536, 58.94617511, 57.97784118, 58.79887164, 59.39506522, 60.23987035, 59.19241983, 60.00853997, 60.54208078, 61.38309268, 60.27258448, 61.08365184, 61.18539177, 61.99030945, 62.38866111, 63.22083015, 61.95057772, 62.74946016, 63.07575895, 63.90312906, 62.53426577, 63.32621674, 63.58148052, 64.40324429]) - s2:cloud_shadow_percentage(time)object0.014343 0 0 ... 0.171499 0.702474
array([0.014343, 0, 0, 0, 0.054097, 4.605516, 0.698502, 4.313568, 0, 0.192556, 1.425056, 2.190543, 3.370393, 5.307427, 4.003611, 6.188291, 3.834939, 6.481926, 6.304014, 3.334409, 1.067575, 5.455423, 5.184477, 2.967202, 5.269652, 6.123294, 4.833765, 8.777347, 1.614719, 0, 4.273178, 2.186992, 1.03513, 0, 1.959071, 0.788833, 1.559536, 5.100645, 4.661606, 3.216317, 2.776483, 4.770232, 0.253128, 2.472405, 2.822181, 1.190196, 4.555168, 2.27717, 3.325294, 3.058549, 1.255206, 0, 2.312093, 6.057649, 1.681954, 0.00354, 0.062443, 0.176702, 4.441281, 0.003873, 0.01506, 1.366059, 4.407515, 5.935782, 2.191183, 0.960863, 0.777035, 0.185627, 0.084436, 2.594633, 3.212657, 0, 0.176088, 3.664836, 2.592776, 1.055455, 0.307066, 0.350476, 0.001083, 0.832782, 2.096626, 0, 0, 0.369065, 1.393818, 1.191167, 0.010585, 0.991542, 0.010255, 1.648835, 1.982648, 0, 0, 0, 0, 2.289101, 0.844747, 2.534806, 2.193481, 0.171499, 0.702474], dtype=object) - s2:datatake_type()<U8'INS-NOBS'
array('INS-NOBS', dtype='<U8') - s2:reflectance_conversion_factor(time)float641.031 1.031 1.031 ... 0.9722 0.9722
array([1.03108911, 1.03108911, 1.03056771, 1.03056771, 1.0297125 , 1.0297125 , 1.02910139, 1.02910139, 1.02811462, 1.02811462, 1.02741898, 1.02741898, 1.02630891, 1.02630891, 1.02553445, 1.02553445, 1.02431023, 1.02431023, 1.02346338, 1.02213494, 1.02213494, 1.02122246, 1.02122246, 1.01980073, 1.01980073, 1.01883016, 1.01883016, 1.01732648, 1.01732648, 1.01630559, 1.01630559, 1.01473201, 1.01473201, 1.01366884, 1.01366884, 1.01203777, 1.01203777, 1.01094064, 1.01094064, 1.00926479, 1.00926479, 1.00814235, 1.00814235, 1.00643462, 1.00643462, 1.00643462, 1.00643462, 1.00529525, 1.00529525, 1.00356865, 1.00356865, 1.00242111, 1.00242111, 1.00068867, 1.00068867, 0.99954146, 0.99954146, 0.9978159 , 0.9978159 , 0.99667754, 0.99667754, 0.99497156, 0.99497156, 0.99385033, 0.99385033, 0.99217627, 0.99217627, 0.99108016, 0.99108016, 0.98944997, 0.98944997, 0.98838681, 0.98838681, 0.98681196, 0.98681196, 0.98578914, 0.98578914, 0.98428059, 0.98428059, 0.98330518, 0.98330518, 0.98187336, 0.98187336, 0.98095209, 0.98095209, 0.97960662, 0.97960662, 0.97874564, 0.97874564, 0.97670079, 0.97670079, 0.97555451, 0.97555451, 0.97483095, 0.97483095, 0.97379601, 0.97379601, 0.97314856, 0.97314856, 0.97223163, 0.97223163]) - instruments()<U3'msi'
array('msi', dtype='<U3') - s2:not_vegetated_percentage(time)object0.121881 0.130712 ... 0.475272
array([0.121881, 0.130712, 0.002947, 0.012857, 0.818665, 3.017239, 0.838188, 2.287781, 0.00929, 0.431038, 0.221677, 0.820877, 1.749901, 4.444554, 1.995795, 9.232897, 1.628613, 10.284705, 10.190202, 1.445566, 0.499206, 4.634994, 14.832933, 2.213302, 12.55146, 4.266572, 13.36088, 5.756466, 0.57309, 0.000255, 9.001599, 1.2693, 2.304426, 0, 9.02485, 0.321276, 1.711434, 6.104159, 13.570227, 8.191615, 17.157021, 14.309764, 0.147671, 17.832597, 7.333148, 3.212517, 6.223135, 16.072802, 7.993152, 4.955937, 1.989888, 1.3e-05, 2.574685, 5.277299, 0.753317, 0.024728, 0.154474, 0.171935, 3.44087, 0.046602, 0.040113, 1.88282, 5.503632, 7.353356, 7.825606, 3.605929, 2.758916, 1.305458, 0.036161, 0.949147, 4.067833, 0.004413, 0.104193, 4.18537, 5.825366, 0.491819, 0.136084, 1.073171, 0.276949, 0.596743, 1.453662, 0.000461, 0.001672, 0.186628, 4.843919, 1.277421, 0.00816, 1.322348, 0.047389, 5.871901, 6.587866, 0, 0, 0.010151, 0.049018, 5.322111, 7.405828, 6.486247, 6.93645, 0.114449, 0.475272], dtype=object) - constellation()<U10'sentinel-2'
array('sentinel-2', dtype='<U10') - mgrs:utm_zone()int6432
array(32)
- s2:datastrip_id(time)<U64'S2B_OPER_MSI_L2A_DS_SGS__201902...
array(['S2B_OPER_MSI_L2A_DS_SGS__20190201T125655_S20190201T102243_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190201T125655_S20190201T102243_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190203T124425_S20190203T101608_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190203T124425_S20190203T101608_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190206T132004_S20190206T102327_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190206T132004_S20190206T102327_N02.11', 'S2B_OPER_MSI_L2A_DS_MPS__20190208T132121_S20190208T101158_N02.11', 'S2B_OPER_MSI_L2A_DS_MPS__20190208T132121_S20190208T101158_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190211T143627_S20190211T102246_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190211T143627_S20190211T102246_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190213T162253_S20190213T101610_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190213T162253_S20190213T101610_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190216T130428_S20190216T102131_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190216T130428_S20190216T102131_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190218T161620_S20190218T101421_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190218T161620_S20190218T101421_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190221T162447_S20190221T102520_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190221T162447_S20190221T102520_N02.11', 'S2A_OPER_MSI_L2A_DS_MPS__20190223T134548_S20190223T101729_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190226T143434_S20190226T102019_N02.11', ... 'S2B_OPER_MSI_L2A_DS_MPS__20190512T134103_S20190512T102248_N02.12', 'S2A_OPER_MSI_L2A_DS_MPS__20190514T134657_S20190514T101441_N02.12', 'S2A_OPER_MSI_L2A_DS_MPS__20190514T134657_S20190514T101441_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190517T131216_S20190517T102508_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190517T131216_S20190517T102508_N02.12', 'S2B_OPER_MSI_L2A_DS_MPS__20190519T132053_S20190519T101033_N02.12', 'S2B_OPER_MSI_L2A_DS_MPS__20190519T132053_S20190519T101033_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190524T130304_S20190524T101701_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190524T130304_S20190524T101701_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190527T145156_S20190527T102026_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190527T145156_S20190527T102026_N02.12', 'S2B_OPER_MSI_L2A_DS_SGS__20190529T143958_S20190529T101637_N02.12', 'S2B_OPER_MSI_L2A_DS_SGS__20190529T143958_S20190529T101637_N02.12', 'S2B_OPER_MSI_L2A_DS_MPS__20190601T135040_S20190601T102031_N02.12', 'S2B_OPER_MSI_L2A_DS_MPS__20190601T135040_S20190601T102031_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190603T130327_S20190603T101642_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190603T130327_S20190603T101642_N02.12', 'S2A_OPER_MSI_L2A_DS_MPS__20190606T134450_S20190606T102358_N02.12', 'S2A_OPER_MSI_L2A_DS_MPS__20190606T134450_S20190606T102358_N02.12'], dtype='<U64') - s2:water_percentage(time)object0.000192 0 0 ... 0.018796 0.058846
array([0.000192, 0, 0, 0.000484, 1.017965, 1.816523, 1.899341, 1.497153, 6e-05, 0.009848, 2.785423, 0.651507, 2.181987, 0.778276, 2.447255, 1.235006, 1.828879, 0.903938, 0.837586, 0.791285, 0.853327, 1.730886, 0.65733, 0.514093, 0.293363, 1.636728, 0.637001, 1.1716, 0.513652, 0, 0.164873, 0.401024, 0.050523, 0, 0.173052, 0.329163, 0.129146, 0.897091, 0.259702, 0.98375, 0.334246, 0.448729, 0.044065, 0.307843, 0.08656, 0.088224, 0.652947, 0.242375, 0.869662, 0.638963, 0.069514, 0, 0.29537, 0.913488, 0.106748, 0.004177, 0.004908, 0.012429, 0.20058, 0.003194, 0.004638, 0.362816, 0.92161, 0.772722, 0.994909, 0.133682, 0.15932, 0.379414, 0.002223, 0.218968, 0.344684, 0.009376, 0.006447, 0.742066, 0.565763, 0.174961, 0.027206, 0.282649, 0.011158, 0.13001, 0.128264, 0, 0, 0.030364, 0.298453, 0.344691, 0.001257, 0.271203, 0.003447, 1.050406, 0.597798, 0, 0, 0.00147, 0.001433, 0.916469, 0.398205, 1.264722, 0.621998, 0.018796, 0.058846], dtype=object) - s2:product_type()<U7'S2MSI2A'
array('S2MSI2A', dtype='<U7') - created(time)<U24'2022-11-08T12:14:57.099Z' ... '...
array(['2022-11-08T12:14:57.099Z', '2022-11-08T12:07:15.671Z', '2022-11-08T11:58:42.239Z', '2022-11-08T11:52:31.873Z', '2022-11-08T11:58:53.378Z', '2022-11-08T11:52:21.920Z', '2022-11-08T11:58:53.183Z', '2022-11-08T12:05:25.354Z', '2022-11-08T11:58:38.817Z', '2022-11-08T12:07:19.166Z', '2022-11-08T11:58:38.972Z', '2022-11-08T11:49:31.028Z', '2022-11-08T12:00:56.277Z', '2022-11-03T09:55:31.023Z', '2022-11-03T11:08:00.382Z', '2022-11-08T12:07:18.675Z', '2022-11-08T12:00:33.368Z', '2022-11-08T12:07:21.011Z', '2022-11-08T12:05:37.791Z', '2022-11-03T11:11:05.412Z', '2022-11-03T10:10:43.801Z', '2022-11-08T11:58:38.091Z', '2022-11-03T10:23:18.376Z', '2022-11-08T11:58:53.430Z', '2022-11-08T12:05:32.318Z', '2022-11-08T11:59:26.092Z', '2022-11-08T11:51:02.353Z', '2022-11-08T11:50:46.933Z', '2022-11-08T12:15:05.389Z', '2022-11-08T11:58:46.175Z', '2022-11-08T12:05:32.031Z', '2022-11-08T11:58:42.836Z', '2022-11-08T12:06:07.127Z', '2022-11-08T12:16:43.099Z', '2022-11-08T12:06:06.731Z', '2022-11-08T12:16:42.257Z', '2022-11-08T11:49:40.179Z', '2022-11-08T12:01:02.143Z', '2022-11-08T11:49:37.014Z', '2022-11-08T12:01:02.928Z', ... '2022-11-08T11:52:40.408Z', '2022-11-08T11:49:50.068Z', '2022-11-08T12:02:19.750Z', '2022-11-08T12:07:28.698Z', '2022-11-08T12:00:10.208Z', '2022-11-08T12:15:16.747Z', '2022-11-03T10:13:09.527Z', '2022-11-08T12:15:12.852Z', '2022-11-03T10:13:06.703Z', '2022-11-08T11:59:21.436Z', '2022-11-08T11:50:19.185Z', '2022-11-08T12:15:16.737Z', '2022-11-08T11:51:16.405Z', '2022-11-08T11:58:50.572Z', '2022-11-08T11:50:40.069Z', '2022-11-03T11:06:08.579Z', '2022-11-08T11:51:46.114Z', '2022-11-08T12:00:09.471Z', '2022-11-08T11:51:45.682Z', '2022-11-08T12:02:23.263Z', '2022-11-08T12:06:47.113Z', '2022-11-08T12:02:23.988Z', '2022-11-08T11:52:02.349Z', '2022-11-08T11:58:48.381Z', '2022-11-08T11:51:45.394Z', '2022-11-08T11:58:51.691Z', '2022-11-08T11:51:14.010Z', '2022-11-08T12:15:17.288Z', '2022-11-08T11:50:08.078Z', '2022-11-08T12:16:04.090Z', '2022-11-08T11:50:06.979Z', '2022-11-08T12:16:04.002Z', '2022-11-08T11:50:39.650Z', '2022-11-08T12:00:15.273Z', '2022-11-03T10:26:49.137Z', '2022-11-08T12:16:10.906Z', '2022-11-08T11:50:14.408Z', '2022-11-08T12:01:59.464Z', '2022-11-08T11:51:35.276Z'], dtype='<U24') - mgrs:latitude_band()<U1'T'
array('T', dtype='<U1') - s2:granule_id(time)<U62'S2B_OPER_MSI_L2A_TL_SGS__201902...
array(['S2B_OPER_MSI_L2A_TL_SGS__20190201T125655_A009958_T32TPT_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190201T125655_A009958_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190203T124425_A018895_T32TPT_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190203T124425_A018895_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190206T132004_A018938_T32TPT_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190206T132004_A018938_T32TPS_N02.11', 'S2B_OPER_MSI_L2A_TL_MPS__20190208T132121_A010058_T32TPT_N02.11', 'S2B_OPER_MSI_L2A_TL_MPS__20190208T132121_A010058_T32TPS_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190211T143627_A010101_T32TPT_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190211T143627_A010101_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190213T162253_A019038_T32TPT_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190213T162253_A019038_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190216T130428_A019081_T32TPT_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190216T130428_A019081_T32TPS_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190218T161620_A010201_T32TPT_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190218T161620_A010201_T32TPS_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190221T162447_A010244_T32TPT_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190221T162447_A010244_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_MPS__20190223T134548_A019181_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190226T143434_A019224_T32TPT_N02.11', ... 'S2B_OPER_MSI_L2A_TL_MPS__20190512T134103_A011388_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_MPS__20190514T134657_A020325_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_MPS__20190514T134657_A020325_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190517T131216_A020368_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190517T131216_A020368_T32TPS_N02.12', 'S2B_OPER_MSI_L2A_TL_MPS__20190519T132053_A011488_T32TPT_N02.12', 'S2B_OPER_MSI_L2A_TL_MPS__20190519T132053_A011488_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190524T130304_A020468_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190524T130304_A020468_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190527T145156_A020511_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190527T145156_A020511_T32TPS_N02.12', 'S2B_OPER_MSI_L2A_TL_SGS__20190529T143958_A011631_T32TPT_N02.12', 'S2B_OPER_MSI_L2A_TL_SGS__20190529T143958_A011631_T32TPS_N02.12', 'S2B_OPER_MSI_L2A_TL_MPS__20190601T135040_A011674_T32TPT_N02.12', 'S2B_OPER_MSI_L2A_TL_MPS__20190601T135040_A011674_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190603T130327_A020611_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190603T130327_A020611_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_MPS__20190606T134450_A020654_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_MPS__20190606T134450_A020654_T32TPS_N02.12'], dtype='<U62') - s2:sequence(time)<U1'0' '0' '0' '0' ... '0' '0' '0' '0'
array(['0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0'], dtype='<U1') - s2:processing_baseline(time)<U5'02.11' '02.11' ... '02.12' '02.12'
array(['02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12'], dtype='<U5') - proj:epsg()int6432632
array(32632)
- gsd()objectNone
array(None, dtype=object)
- raster:bands()object{'nodata': 0, 'data_type': 'uint...
array({'nodata': 0, 'data_type': 'uint8', 'spatial_resolution': 20}, dtype=object) - title()<U30'Scene classification map (SCL)'
array('Scene classification map (SCL)', dtype='<U30') - common_name()objectNone
array(None, dtype=object)
- center_wavelength()objectNone
array(None, dtype=object)
- full_width_half_max()objectNone
array(None, dtype=object)
- epsg()int6432632
array(32632)
- spatial_ref()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 32N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",9],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32632"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 32N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 9.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 32N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",9],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32632"]]
array(0)
- timePandasIndex
PandasIndex(DatetimeIndex(['2019-02-01 10:27:41.665000', '2019-02-01 10:27:55.803000', '2019-02-03 10:17:41.721000', '2019-02-03 10:17:56.196000', '2019-02-06 10:27:38.251000', '2019-02-06 10:27:52.378000', '2019-02-08 10:17:45.015000', '2019-02-08 10:17:59.486000', '2019-02-11 10:27:41.425000', '2019-02-11 10:27:55.562000', ... '2019-05-27 10:27:44.339000', '2019-05-27 10:27:58.464000', '2019-05-29 10:17:53.232000', '2019-05-29 10:18:07.701000', '2019-06-01 10:27:49.632000', '2019-06-01 10:28:03.768000', '2019-06-03 10:17:47.026000', '2019-06-03 10:18:01.498000', '2019-06-06 10:27:43.405000', '2019-06-06 10:27:57.521000'], dtype='datetime64[ns]', name='time', length=101, freq=None)) - xPandasIndex
PandasIndex(Index([653760.0, 653780.0, 653800.0, 653820.0, 653840.0, 653860.0, 653880.0, 653900.0, 653920.0, 653940.0, ... 680900.0, 680920.0, 680940.0, 680960.0, 680980.0, 681000.0, 681020.0, 681040.0, 681060.0, 681080.0], dtype='float64', name='x', length=1367)) - yPandasIndex
PandasIndex(Index([5202800.0, 5202780.0, 5202760.0, 5202740.0, 5202720.0, 5202700.0, 5202680.0, 5202660.0, 5202640.0, 5202620.0, ... 5168840.0, 5168820.0, 5168800.0, 5168780.0, 5168760.0, 5168740.0, 5168720.0, 5168700.0, 5168680.0, 5168660.0], dtype='float64', name='y', length=1708))
The clipping is done by the RioXarray library. The RioXarray library is a library that allows to manipulate geospatial data in xarray datasets. Underneath it uses the rasterio library that is a library built on top of GDAL.
snowmap_clipped = snow_cloud.rio.clip([geom_utm32])
It’s time to persist the data in memory. We will use the persist method to load the data in memory and keep it there until the end of the analysis.
clipped_date = snowmap_clipped.persist()
Aggregate data#
Data aggregation is a very important step in the analysis. It allows to reduce the amount of data and to make the analysis more efficient. Moreover as in this case we are going to aggregate the date to daily values, this will allow use to compute statistic on the data at the basin scale later on. The groupby method allows to group the data by a specific dimension. In this case we will group the data by the time dimension, aggregating to the date and removing the time information, once the group is obtained we will aggregate the data by taking the maximum value.
clipped_date.time
<xarray.DataArray 'time' (time: 101)>
array(['2019-02-01T10:27:41.665000000', '2019-02-01T10:27:55.803000000',
'2019-02-03T10:17:41.721000000', '2019-02-03T10:17:56.196000000',
'2019-02-06T10:27:38.251000000', '2019-02-06T10:27:52.378000000',
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Coordinates: (12/51)
* time (time) datetime64[ns] 2019-02-01...
id (time) <U24 'S2B_32TPT_20190201_...
band <U6 'scl'
s2:generation_time (time) <U27 '2019-02-01T12:56:55...
eo:cloud_cover (time) object 94.135713 ... 85.6...
updated (time) <U24 '2022-11-08T12:14:57...
... ...
title <U30 'Scene classification map (...
common_name object None
center_wavelength object None
full_width_half_max object None
epsg int64 32632
spatial_ref int64 0- time: 101
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array('scl', dtype='<U6') - s2:generation_time(time)<U27'2019-02-01T12:56:55.000000Z' .....
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array(['MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS', 'MGRS-32TPT', 'MGRS-32TPS'], dtype='<U10') - s2:unclassified_percentage(time)object0.011951 5.6e-05 ... 2.768176
array([0.011951, 5.6e-05, 0, 0.004409, 2.61864, 5.640598, 4.763902, 4.89477, 0.000737, 1.06698, 6.379969, 3.581112, 3.75781, 4.503651, 3.415961, 5.543773, 6.000673, 6.204186, 5.974628, 4.41536, 1.325105, 4.979029, 5.612632, 4.590277, 6.777608, 6.167155, 6.077614, 6.867857, 2.550018, 0.020529, 6.43759, 2.276966, 2.925147, 0, 3.508973, 2.016566, 3.365213, 5.948313, 5.286334, 3.903815, 4.453562, 5.392561, 0.663991, 4.577908, 3.842456, 2.561705, 5.091375, 5.002561, 4.391824, 5.487678, 3.727499, 0.000222, 3.55055, 6.093498, 5.667936, 0.889327, 0.880247, 0.800342, 5.338126, 0.386644, 0.204943, 4.824572, 4.264689, 3.692116, 4.032218, 8.155444, 6.945007, 0.66158, 0.617971, 3.951247, 4.494771, 0.008768, 1.226688, 4.524324, 4.265018, 2.941594, 1.672861, 3.151683, 1.427331, 1.791112, 4.994049, 0, 7.1e-05, 1.250102, 3.509952, 2.313757, 0.087243, 3.433142, 0.07484, 4.014421, 3.469744, 0, 0, 0.00459, 0.014751, 4.330208, 3.50396, 3.27118, 2.913887, 0.843723, 2.768176], dtype=object) - s2:product_uri(time)<U65'S2B_MSIL2A_20190201T102249_N021...
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array({'sentinel2-to-stac': '0.1.0'}, dtype=object) - platform(time)<U11'sentinel-2b' ... 'sentinel-2a'
array(['sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2b', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a', 'sentinel-2a'], dtype='<U11') - mgrs:grid_square(time)<U2'PT' 'PS' 'PT' ... 'PS' 'PT' 'PS'
array(['PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PS', 'PT', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PS', 'PT', 'PS', 'PS', 'PT', 'PT', 'PS', 'PT', 'PT', 'PS', 'PS', 'PT', 'PT', 'PS', 'PS', 'PT', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PS', 'PT', 'PS', 'PT', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS', 'PT', 'PS'], dtype='<U2') - earthsearch:payload_id(time)<U74'roda-sentinel2/workflow-sentine...
array(['roda-sentinel2/workflow-sentinel2-to-stac/27d818188ce5e85723443ae3ce9f0ec6', 'roda-sentinel2/workflow-sentinel2-to-stac/c7756e556cb03e427209ed59e170bbac', 'roda-sentinel2/workflow-sentinel2-to-stac/6f2157ad2b6798a3d2230af8bd6797ed', 'roda-sentinel2/workflow-sentinel2-to-stac/6a5d17fe220672054478b92f4108c7d9', 'roda-sentinel2/workflow-sentinel2-to-stac/7826aa614df00fbdb372d086b7a7d36c', 'roda-sentinel2/workflow-sentinel2-to-stac/92de56004acdcdd7934c8928cd391cdb', 'roda-sentinel2/workflow-sentinel2-to-stac/9ddf64d74781ce6eac34b1730be320b3', 'roda-sentinel2/workflow-sentinel2-to-stac/5a36ed3a8cf7d067f920b6891b6b70a7', 'roda-sentinel2/workflow-sentinel2-to-stac/4b16e54553d664864a037c49e3e5a3e4', 'roda-sentinel2/workflow-sentinel2-to-stac/643e7785c6fb206e8543216defbaeccd', 'roda-sentinel2/workflow-sentinel2-to-stac/d35f2c7cd794327bd2818fe59c1d0c76', 'roda-sentinel2/workflow-sentinel2-to-stac/aa9a7f78e508d756ed7e8c0a6a61c83f', 'roda-sentinel2/workflow-sentinel2-to-stac/2b8f15de1746ef715d7e077bd9862f6d', 'roda-sentinel2/workflow-sentinel2-to-stac/ba6f3eb9b391095616caef44af5311aa', 'roda-sentinel2/workflow-sentinel2-to-stac/d2971a23a81d5bebae06d2528f2e368e', 'roda-sentinel2/workflow-sentinel2-to-stac/72817018462c5d402beb0343134e585f', 'roda-sentinel2/workflow-sentinel2-to-stac/9b6fde685989ca90bc038419365794c6', 'roda-sentinel2/workflow-sentinel2-to-stac/271b82f8b21483572572340e4bc82e1c', 'roda-sentinel2/workflow-sentinel2-to-stac/d4ee83c1f4cead0ebccf604ac4360205', 'roda-sentinel2/workflow-sentinel2-to-stac/12cea93e0f4bd396fdeb01f2a6f67c87', ... 'roda-sentinel2/workflow-sentinel2-to-stac/c1f054678e1bdce81f354a3a4dd1bce8', 'roda-sentinel2/workflow-sentinel2-to-stac/037578cb265b085965afb824933f3b2c', 'roda-sentinel2/workflow-sentinel2-to-stac/f62aad148421740c02b7680debcf8949', 'roda-sentinel2/workflow-sentinel2-to-stac/3f207fbdf51bacac46e150f212009f2f', 'roda-sentinel2/workflow-sentinel2-to-stac/f00409b96f3eba6f2cfd95125bd3caa1', 'roda-sentinel2/workflow-sentinel2-to-stac/638efb6bd79a1e2c09adf93999760474', 'roda-sentinel2/workflow-sentinel2-to-stac/bbdfc519ad83e508472850f049031f6e', 'roda-sentinel2/workflow-sentinel2-to-stac/8b73a814225ff2dee40f49029932ed2e', 'roda-sentinel2/workflow-sentinel2-to-stac/23b0df7fdadb8d2f1b22d28e1dc7c31c', 'roda-sentinel2/workflow-sentinel2-to-stac/eb058402470acd9b2a2fea3b23236265', 'roda-sentinel2/workflow-sentinel2-to-stac/80dc1fc54946785e70f1f1edc04e33bc', 'roda-sentinel2/workflow-sentinel2-to-stac/a88c46e47e5aebedb99141db3f23345c', 'roda-sentinel2/workflow-sentinel2-to-stac/eaca43368bb48aa6df33d93d80d163bb', 'roda-sentinel2/workflow-sentinel2-to-stac/6ccb82b7b079cc78d5f0942c37ffd957', 'roda-sentinel2/workflow-sentinel2-to-stac/363fd02cca77098ad2211c0fab1ec86a', 'roda-sentinel2/workflow-sentinel2-to-stac/0c64cb510aee8db820ff9a4b0d990319', 'roda-sentinel2/workflow-sentinel2-to-stac/32e00e2b7cc5dba7ed9325bd2bf4eea7', 'roda-sentinel2/workflow-sentinel2-to-stac/5800db9cadefa73a1365d612622c60ec', 'roda-sentinel2/workflow-sentinel2-to-stac/fdb25b0f5b5531b5065244d5331b8f43'], dtype='<U74') - earthsearch:boa_offset_applied()boolFalse
array(False)
- s2:nodata_pixel_percentage(time)object0.000103 10.936822 ... 0 10.651179
array([0.000103, 10.936822, 9.035017, 0, 0.000242, 11.058175, 8.80881, 0.000508, 0.001178, 11.054406, 8.909436, 0.000445, 0.00077, 10.979612, 8.976639, 0.001121, 0.005246, 10.948487, 0.000491, 0.000909, 22.085553, 8.972917, 0.000936, 8.3e-05, 10.811792, 9.105272, 0.000382, 10.160348, 64.006782, 8.880395, 3e-06, 0.000866, 11.102382, 9.613313, 0.003882, 0, 10.357866, 9.515041, 0.001981, 0.000415, 10.554736, 0.000325, 9.277332, 14.97362, 81.199092, 91.406816, 0.268768, 0.000202, 9.107425, 9.6e-05, 10.765276, 0, 9.213974, 7.6e-05, 10.927774, 0, 8.74318, 0.002386, 11.157236, 9.013481, 0, 0.000876, 11.015444, 3.6e-05, 8.53733, 11.414159, 0.006506, 8.831852, 0, 0.001652, 11.207292, 8.347301, 0, 0.009967, 11.529136, 8.854675, 0, 0.001835, 11.179462, 8.174197, 1e-05, 0.014496, 11.674032, 8.956078, 7e-06, 0.000222, 11.040318, 8.240474, 0, 9.063792, 2e-05, 4e-05, 10.885637, 8.353151, 0, 0.007133, 11.447613, 9.397335, 0.000514, 0, 10.651179], dtype=object) - s2:high_proba_clouds_percentage(time)object28.474605 8.089755 ... 68.302697
array([28.474605, 8.089755, 0, 8.097946, 0.347863, 0.404564, 3.18249, 13.025998, 3.795855, 16.476883, 0.722417, 2.996168, 0.191315, 0.345278, 0.378075, 0.524364, 0.404088, 0.428093, 3.221123, 0.411011, 57.985854, 0.479861, 0.58567, 1.164479, 0.555689, 10.933855, 1.66515, 22.881198, 27.283058, 1.001521, 12.859948, 68.552494, 60.841697, 0, 7.293878, 35.636574, 33.464602, 4.723628, 0.727587, 0.27859, 0.293402, 15.131488, 75.048304, 0.320798, 0.283979, 5.256074, 12.557438, 0.493941, 0.414534, 5.949093, 24.334399, 8.32763, 25.453517, 14.401695, 60.160649, 34.283876, 44.987833, 88.686782, 43.836692, 87.367743, 63.687009, 23.234625, 17.33311, 16.457643, 1.604513, 9.021848, 1.382886, 38.881776, 78.495955, 51.282567, 17.579152, 35.019681, 28.828606, 6.963654, 8.859406, 74.317372, 73.920262, 2.810752, 12.166209, 72.222966, 43.735892, 0.74115, 4.254435, 82.502216, 15.15367, 46.63088, 78.458554, 45.790553, 46.282384, 4.590221, 8.36652, 16.94798, 9.10632, 29.857177, 31.819323, 5.42523, 1.85607, 5.484578, 6.884611, 59.161156, 68.302697], dtype=object) - s2:thin_cirrus_percentage(time)object2.225559 0.00928 ... 3.543517
array([2.225559, 0.00928, 0, 0.578814, 25.953317, 1.831257, 13.336582, 1.030075, 0.387741, 11.59085, 0.024961, 11.286602, 1.586686, 16.248183, 0.407614, 0.068627, 0.489496, 0.011881, 0.002253, 17.164983, 5.989625, 0.114574, 0.009983, 20.426282, 9.359232, 0.348671, 0.106944, 0.303773, 0.628434, 0.023274, 4.190633, 1.807296, 5.32212, 0, 3.040526, 1.687068, 2.680191, 1.256244, 2.433099, 0.01925, 0.00013, 0.421204, 0.662916, 0.000457, 0.000494, 0.09278, 3.227772, 2.579917, 2.847647, 6.555422, 11.507395, 0.011569, 3.647571, 2.17389, 0.141721, 1.400944, 1.107897, 1.479772, 3.255056, 0.020041, 0.150142, 10.038469, 0.895554, 0.594219, 0.097929, 5.367009, 24.042393, 8.933073, 1.100103, 2.085489, 1.311102, 0.622414, 3.660977, 4.210678, 0.969822, 0.862668, 0.18908, 15.802597, 6.322686, 0.747905, 0.120408, 0.002718, 0.000169, 1.195515, 0.775482, 3.188232, 0.098726, 5.373817, 0.078095, 1.509326, 0.103639, 0, 0, 0.522361, 1.712088, 0.420649, 0.19434, 0.367874, 0.052555, 0.241005, 3.543517], dtype=object) - view:sun_azimuth(time)float64163.9 163.8 161.1 ... 155.2 154.5
array([163.86054926, 163.77370581, 161.0959049 , 160.99036777, 163.38665794, 163.28917665, 160.62219832, 160.50454567, 162.99215074, 162.88338599, 160.16546807, 160.03450499, 162.62117436, 162.50001042, 159.78640816, 159.64117272, 162.33273248, 162.19862356, 159.26224591, 162.06176346, 161.91360695, 159.13034121, 158.95320803, 161.86499103, 161.7022021 , 158.84327907, 158.64834693, 161.49940361, 161.67789873, 158.62176727, 158.40823407, 161.55839958, 161.36362349, 158.4090363 , 158.17553626, 161.45412428, 161.242065 , 158.23655975, 157.98199941, 161.38517084, 161.15511737, 157.77852687, 158.05563993, 161.05388999, 161.05388999, 161.30338543, 161.30338543, 157.58829308, 157.88941887, 161.23672075, 160.96680719, 157.35575732, 157.68297259, 161.1261513 , 160.83388843, 157.12192929, 157.47688591, 161.01726199, 160.70134413, 157.20224767, 156.81680652, 160.83374584, 160.49155977, 156.49663989, 156.91449294, 160.26509163, 160.63521358, 156.52232228, 156.06857607, 160.3212994 , 159.91957719, 156.10029778, 155.6083854 , 159.97641954, 159.54111816, 155.543096 , 155.00901493, 159.48676354, 159.01354282, 154.95850051, 154.38032857, 158.97177509, 158.45894651, 154.23059859, 153.60472296, 158.30398116, 157.74751327, 153.50105456, 152.82739621, 152.63618058, 151.91278584, 156.81925035, 156.17298279, 151.81293831, 151.04268726, 156.05094177, 155.36170143, 150.89209112, 150.07633929, 155.18144211, 154.45002254]) - s2:datatake_id(time)<U34'GS2B_20190201T102249_009958_N02...
array(['GS2B_20190201T102249_009958_N02.11', 'GS2B_20190201T102249_009958_N02.11', 'GS2A_20190203T101221_018895_N02.11', 'GS2A_20190203T101221_018895_N02.11', 'GS2A_20190206T102211_018938_N02.11', 'GS2A_20190206T102211_018938_N02.11', 'GS2B_20190208T101159_010058_N02.11', 'GS2B_20190208T101159_010058_N02.11', 'GS2B_20190211T102149_010101_N02.11', 'GS2B_20190211T102149_010101_N02.11', 'GS2A_20190213T101131_019038_N02.11', 'GS2A_20190213T101131_019038_N02.11', 'GS2A_20190216T102111_019081_N02.11', 'GS2A_20190216T102111_019081_N02.11', 'GS2B_20190218T101059_010201_N02.11', 'GS2B_20190218T101059_010201_N02.11', 'GS2B_20190221T102039_010244_N02.11', 'GS2B_20190221T102039_010244_N02.11', 'GS2A_20190223T101021_019181_N02.11', 'GS2A_20190226T102021_019224_N02.11', ... 'GS2B_20190512T102029_011388_N02.12', 'GS2B_20190512T102029_011388_N02.12', 'GS2A_20190514T101031_020325_N02.12', 'GS2A_20190514T101031_020325_N02.12', 'GS2A_20190517T102031_020368_N02.12', 'GS2A_20190517T102031_020368_N02.12', 'GS2B_20190519T101039_011488_N02.12', 'GS2B_20190519T101039_011488_N02.12', 'GS2A_20190524T101031_020468_N02.12', 'GS2A_20190524T101031_020468_N02.12', 'GS2A_20190527T102031_020511_N02.12', 'GS2A_20190527T102031_020511_N02.12', 'GS2B_20190529T101039_011631_N02.12', 'GS2B_20190529T101039_011631_N02.12', 'GS2B_20190601T102029_011674_N02.12', 'GS2B_20190601T102029_011674_N02.12', 'GS2A_20190603T101031_020611_N02.12', 'GS2A_20190603T101031_020611_N02.12', 'GS2A_20190606T102031_020654_N02.12', 'GS2A_20190606T102031_020654_N02.12'], dtype='<U34') - earthsearch:s3_path(time)<U79's3://sentinel-cogs/sentinel-s2-...
array(['s3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2B_32TPT_20190201_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2B_32TPS_20190201_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2A_32TPT_20190203_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2A_32TPS_20190203_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2A_32TPT_20190206_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2A_32TPS_20190206_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2B_32TPT_20190208_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2B_32TPS_20190208_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2B_32TPT_20190211_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2B_32TPS_20190211_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2A_32TPT_20190213_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2A_32TPS_20190213_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2A_32TPT_20190216_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2A_32TPS_20190216_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2B_32TPT_20190218_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2B_32TPS_20190218_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2B_32TPT_20190221_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2B_32TPS_20190221_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/2/S2A_32TPS_20190223_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/2/S2A_32TPT_20190226_0_L2A', ... 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2B_32TPS_20190512_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2A_32TPT_20190514_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2A_32TPS_20190514_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2A_32TPT_20190517_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2A_32TPS_20190517_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2B_32TPT_20190519_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2B_32TPS_20190519_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2A_32TPT_20190524_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2A_32TPS_20190524_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2A_32TPT_20190527_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2A_32TPS_20190527_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/5/S2B_32TPT_20190529_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/5/S2B_32TPS_20190529_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/6/S2B_32TPT_20190601_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/6/S2B_32TPS_20190601_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/6/S2A_32TPT_20190603_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/6/S2A_32TPS_20190603_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PT/2019/6/S2A_32TPT_20190606_0_L2A', 's3://sentinel-cogs/sentinel-s2-l2a-cogs/32/T/PS/2019/6/S2A_32TPS_20190606_0_L2A'], dtype='<U79') - s2:dark_features_percentage(time)object1.308534 1.237797 ... 0.220692
array([1.308534, 1.237797, 0.034161, 0.101277, 7.692839, 20.851712, 13.294898, 15.587787, 0.077034, 1.723071, 19.534473, 12.280087, 21.493369, 19.257888, 22.405481, 20.790145, 18.783672, 20.127527, 18.078911, 12.080093, 4.725911, 17.626123, 17.116198, 5.873704, 13.002147, 10.222468, 13.593714, 8.990999, 6.079657, 0, 6.460854, 1.464981, 2.777434, 4e-06, 3.861269, 1.383761, 3.679705, 11.617623, 11.908567, 9.980234, 10.250788, 6.9092, 0.526073, 9.682282, 9.566194, 9.52535, 7.10426, 7.071975, 6.436816, 4.253971, 1.748624, 0.005153, 1.790272, 4.358801, 1.404547, 0.219084, 0.448807, 0.20305, 2.875947, 0.144373, 0.170593, 1.528588, 3.836949, 3.519545, 3.9237, 2.545508, 1.299646, 0.459325, 0.262378, 0.76153, 1.888499, 0.024142, 0.096446, 2.514954, 2.197189, 0.238995, 0.140663, 0.641695, 0.350758, 0.326455, 0.696136, 0.002008, 0.003858, 0.150131, 0.984025, 0.647242, 0.072917, 0.399238, 0.027993, 1.183329, 1.05573, 0, 0, 0, 3e-05, 1.654051, 1.453961, 1.081163, 0.874341, 0.107568, 0.220692], dtype=object) - s2:snow_ice_percentage(time)object4.407356 2.352311 ... 5.44832
array([4.407356, 2.352311, 0.05931, 12.186134, 47.520396, 43.431687, 52.38657, 43.825087, 1.947754, 14.116633, 63.632268, 37.590456, 47.635952, 26.882216, 48.269284, 41.128185, 60.625523, 43.958402, 41.597959, 54.815727, 15.990245, 52.539939, 38.421527, 45.304981, 40.83612, 45.512161, 35.859022, 37.780914, 54.080808, 0.170379, 20.941679, 8.076091, 11.862913, 0, 15.792303, 23.095481, 24.48242, 27.64447, 16.406852, 43.97696, 37.887084, 29.257828, 19.569986, 30.404931, 40.028054, 45.201612, 30.308124, 32.947722, 42.572933, 31.911319, 15.898545, 0.318708, 16.770558, 35.886163, 21.665148, 15.876842, 10.93374, 5.938221, 22.171693, 7.896252, 6.257269, 32.861185, 37.115005, 26.511607, 35.428345, 30.256045, 35.58833, 2.863022, 2.96781, 24.319336, 28.161886, 22.244364, 11.430284, 35.204297, 34.353489, 8.778142, 15.177004, 28.84759, 14.091474, 11.922268, 27.344078, 16.512518, 0.642247, 6.355498, 26.708639, 10.856315, 1.016905, 15.551555, 13.515091, 31.784019, 31.038001, 0, 0.006393, 18.458416, 24.612381, 27.292523, 30.283567, 25.201038, 25.072944, 3.380935, 5.44832], dtype=object) - s2:vegetation_percentage(time)object3.3e-05 0 0 ... 0.467271 4.627483
array([3.3e-05, 0, 0, 0, 0.129419, 3.024495, 1.335275, 3.476257, 0, 0.01874, 2.591085, 1.74686, 5.702759, 3.2968, 8.140194, 11.361623, 5.147837, 10.961309, 12.244289, 3.050694, 0.248903, 11.782508, 16.640516, 4.321283, 9.398247, 10.729123, 19.324329, 3.294571, 1.031084, 0, 8.106805, 4.785185, 1.40766, 0, 10.630693, 0.949234, 1.002168, 15.971488, 21.30038, 28.449246, 24.982615, 20.921379, 0.170554, 27.42599, 18.105584, 1.673402, 18.766998, 28.619561, 28.29192, 20.392635, 0.89143, 0, 7.852823, 20.350888, 2.709706, 0.032896, 0.085879, 1.107229, 10.944532, 0.00889, 0.031118, 8.703066, 22.132467, 27.114123, 39.840275, 16.156347, 7.824096, 13.115945, 0.312189, 7.707577, 29.86159, 0, 0.554955, 33.616117, 36.617664, 4.994705, 0.884974, 15.074661, 0.021281, 4.312731, 12.670155, 0, 0, 1.434204, 38.958597, 17.746092, 0.014001, 9.718411, 0.010922, 47.022659, 45.318523, 0, 0, 0, 0, 50.448912, 53.186417, 53.010529, 53.090888, 0.467271, 4.627483], dtype=object) - s2:medium_proba_clouds_percentage(time)float6463.44 88.18 99.9 ... 35.49 13.85
array([63.435549, 88.180089, 99.903584, 79.01808 , 13.846792, 15.376405, 8.264255, 10.061523, 93.781531, 54.373395, 2.682665, 26.855788, 12.329829, 18.935725, 8.53673 , 3.927092, 1.256269, 0.638028, 1.549034, 2.490874, 11.31425 , 0.656667, 0.938735, 12.62439 , 1.956482, 4.059975, 4.541585, 4.175279, 5.645482, 98.784047, 27.562839, 9.179667, 11.472946, 99.999994, 44.715387, 33.792046, 27.925593, 20.736341, 23.445642, 1.00022 , 1.864669, 2.437614, 2.913307, 6.97479 , 17.931353, 31.198141, 11.512786, 4.691971, 2.856221, 16.796426, 38.577497, 91.336703, 35.752556, 4.486631, 5.708276, 47.264585, 41.333771, 1.423543, 3.495222, 4.122388, 29.439113, 15.1978 , 3.58947 , 8.048888, 4.061321, 23.797327, 19.222367, 33.214778, 16.120769, 6.12951 , 9.077822, 42.066842, 53.915316, 4.373706, 3.753505, 6.14429 , 7.544799, 31.964722, 65.331072, 7.117034, 6.760735, 82.741141, 95.097548, 6.526285, 7.373446, 15.804207, 20.231655, 17.148194, 39.949581, 1.324885, 1.479531, 83.052021, 90.887284, 51.145834, 41.790977, 1.900746, 0.872907, 1.297867, 1.358848, 35.4936 , 13.852519]) - s2:degraded_msi_data_percentage()int640
array(0)
- s2:saturated_defective_pixel_percentage()int640
array(0)
- view:sun_elevation(time)float6424.07 24.94 24.11 ... 63.58 64.4
array([24.07241972, 24.94141661, 24.11166869, 24.9684836 , 25.49664938, 26.36366484, 25.57962234, 26.4341079 , 27.04993803, 27.9152628 , 27.16076928, 28.01296315, 28.70727321, 29.5709547 , 28.85348803, 29.70371374, 30.46485883, 31.32723973, 31.47808545, 32.29666219, 33.15779068, 32.48780958, 33.33453363, 34.19914284, 35.0593373 , 34.39936888, 35.24450457, 37.00534716, 36.14604869, 36.36263943, 37.20653153, 38.13331346, 38.99201242, 38.35138608, 39.19406169, 40.13740372, 40.99556917, 40.35799918, 41.19965614, 42.14830171, 43.0061052 , 43.20051401, 42.35991933, 45.00335051, 45.00335051, 44.1459899 , 44.1459899 , 45.18941908, 44.34983468, 46.12283814, 46.97983296, 47.14319961, 46.30486231, 48.05706655, 48.9134756 , 49.05721314, 48.22013551, 49.94325734, 50.79908113, 50.07054724, 50.90593871, 51.75765811, 52.61252027, 52.68747307, 51.85386678, 54.35148517, 53.49767167, 53.54317197, 54.37433061, 55.13859946, 55.99075571, 55.14060577, 55.9690822 , 56.68123536, 57.53155135, 56.61669955, 57.44159327, 58.09850536, 58.94617511, 57.97784118, 58.79887164, 59.39506522, 60.23987035, 59.19241983, 60.00853997, 60.54208078, 61.38309268, 60.27258448, 61.08365184, 61.18539177, 61.99030945, 62.38866111, 63.22083015, 61.95057772, 62.74946016, 63.07575895, 63.90312906, 62.53426577, 63.32621674, 63.58148052, 64.40324429]) - s2:cloud_shadow_percentage(time)object0.014343 0 0 ... 0.171499 0.702474
array([0.014343, 0, 0, 0, 0.054097, 4.605516, 0.698502, 4.313568, 0, 0.192556, 1.425056, 2.190543, 3.370393, 5.307427, 4.003611, 6.188291, 3.834939, 6.481926, 6.304014, 3.334409, 1.067575, 5.455423, 5.184477, 2.967202, 5.269652, 6.123294, 4.833765, 8.777347, 1.614719, 0, 4.273178, 2.186992, 1.03513, 0, 1.959071, 0.788833, 1.559536, 5.100645, 4.661606, 3.216317, 2.776483, 4.770232, 0.253128, 2.472405, 2.822181, 1.190196, 4.555168, 2.27717, 3.325294, 3.058549, 1.255206, 0, 2.312093, 6.057649, 1.681954, 0.00354, 0.062443, 0.176702, 4.441281, 0.003873, 0.01506, 1.366059, 4.407515, 5.935782, 2.191183, 0.960863, 0.777035, 0.185627, 0.084436, 2.594633, 3.212657, 0, 0.176088, 3.664836, 2.592776, 1.055455, 0.307066, 0.350476, 0.001083, 0.832782, 2.096626, 0, 0, 0.369065, 1.393818, 1.191167, 0.010585, 0.991542, 0.010255, 1.648835, 1.982648, 0, 0, 0, 0, 2.289101, 0.844747, 2.534806, 2.193481, 0.171499, 0.702474], dtype=object) - s2:datatake_type()<U8'INS-NOBS'
array('INS-NOBS', dtype='<U8') - s2:reflectance_conversion_factor(time)float641.031 1.031 1.031 ... 0.9722 0.9722
array([1.03108911, 1.03108911, 1.03056771, 1.03056771, 1.0297125 , 1.0297125 , 1.02910139, 1.02910139, 1.02811462, 1.02811462, 1.02741898, 1.02741898, 1.02630891, 1.02630891, 1.02553445, 1.02553445, 1.02431023, 1.02431023, 1.02346338, 1.02213494, 1.02213494, 1.02122246, 1.02122246, 1.01980073, 1.01980073, 1.01883016, 1.01883016, 1.01732648, 1.01732648, 1.01630559, 1.01630559, 1.01473201, 1.01473201, 1.01366884, 1.01366884, 1.01203777, 1.01203777, 1.01094064, 1.01094064, 1.00926479, 1.00926479, 1.00814235, 1.00814235, 1.00643462, 1.00643462, 1.00643462, 1.00643462, 1.00529525, 1.00529525, 1.00356865, 1.00356865, 1.00242111, 1.00242111, 1.00068867, 1.00068867, 0.99954146, 0.99954146, 0.9978159 , 0.9978159 , 0.99667754, 0.99667754, 0.99497156, 0.99497156, 0.99385033, 0.99385033, 0.99217627, 0.99217627, 0.99108016, 0.99108016, 0.98944997, 0.98944997, 0.98838681, 0.98838681, 0.98681196, 0.98681196, 0.98578914, 0.98578914, 0.98428059, 0.98428059, 0.98330518, 0.98330518, 0.98187336, 0.98187336, 0.98095209, 0.98095209, 0.97960662, 0.97960662, 0.97874564, 0.97874564, 0.97670079, 0.97670079, 0.97555451, 0.97555451, 0.97483095, 0.97483095, 0.97379601, 0.97379601, 0.97314856, 0.97314856, 0.97223163, 0.97223163]) - instruments()<U3'msi'
array('msi', dtype='<U3') - s2:not_vegetated_percentage(time)object0.121881 0.130712 ... 0.475272
array([0.121881, 0.130712, 0.002947, 0.012857, 0.818665, 3.017239, 0.838188, 2.287781, 0.00929, 0.431038, 0.221677, 0.820877, 1.749901, 4.444554, 1.995795, 9.232897, 1.628613, 10.284705, 10.190202, 1.445566, 0.499206, 4.634994, 14.832933, 2.213302, 12.55146, 4.266572, 13.36088, 5.756466, 0.57309, 0.000255, 9.001599, 1.2693, 2.304426, 0, 9.02485, 0.321276, 1.711434, 6.104159, 13.570227, 8.191615, 17.157021, 14.309764, 0.147671, 17.832597, 7.333148, 3.212517, 6.223135, 16.072802, 7.993152, 4.955937, 1.989888, 1.3e-05, 2.574685, 5.277299, 0.753317, 0.024728, 0.154474, 0.171935, 3.44087, 0.046602, 0.040113, 1.88282, 5.503632, 7.353356, 7.825606, 3.605929, 2.758916, 1.305458, 0.036161, 0.949147, 4.067833, 0.004413, 0.104193, 4.18537, 5.825366, 0.491819, 0.136084, 1.073171, 0.276949, 0.596743, 1.453662, 0.000461, 0.001672, 0.186628, 4.843919, 1.277421, 0.00816, 1.322348, 0.047389, 5.871901, 6.587866, 0, 0, 0.010151, 0.049018, 5.322111, 7.405828, 6.486247, 6.93645, 0.114449, 0.475272], dtype=object) - constellation()<U10'sentinel-2'
array('sentinel-2', dtype='<U10') - mgrs:utm_zone()int6432
array(32)
- s2:datastrip_id(time)<U64'S2B_OPER_MSI_L2A_DS_SGS__201902...
array(['S2B_OPER_MSI_L2A_DS_SGS__20190201T125655_S20190201T102243_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190201T125655_S20190201T102243_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190203T124425_S20190203T101608_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190203T124425_S20190203T101608_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190206T132004_S20190206T102327_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190206T132004_S20190206T102327_N02.11', 'S2B_OPER_MSI_L2A_DS_MPS__20190208T132121_S20190208T101158_N02.11', 'S2B_OPER_MSI_L2A_DS_MPS__20190208T132121_S20190208T101158_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190211T143627_S20190211T102246_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190211T143627_S20190211T102246_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190213T162253_S20190213T101610_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190213T162253_S20190213T101610_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190216T130428_S20190216T102131_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190216T130428_S20190216T102131_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190218T161620_S20190218T101421_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190218T161620_S20190218T101421_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190221T162447_S20190221T102520_N02.11', 'S2B_OPER_MSI_L2A_DS_SGS__20190221T162447_S20190221T102520_N02.11', 'S2A_OPER_MSI_L2A_DS_MPS__20190223T134548_S20190223T101729_N02.11', 'S2A_OPER_MSI_L2A_DS_SGS__20190226T143434_S20190226T102019_N02.11', ... 'S2B_OPER_MSI_L2A_DS_MPS__20190512T134103_S20190512T102248_N02.12', 'S2A_OPER_MSI_L2A_DS_MPS__20190514T134657_S20190514T101441_N02.12', 'S2A_OPER_MSI_L2A_DS_MPS__20190514T134657_S20190514T101441_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190517T131216_S20190517T102508_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190517T131216_S20190517T102508_N02.12', 'S2B_OPER_MSI_L2A_DS_MPS__20190519T132053_S20190519T101033_N02.12', 'S2B_OPER_MSI_L2A_DS_MPS__20190519T132053_S20190519T101033_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190524T130304_S20190524T101701_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190524T130304_S20190524T101701_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190527T145156_S20190527T102026_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190527T145156_S20190527T102026_N02.12', 'S2B_OPER_MSI_L2A_DS_SGS__20190529T143958_S20190529T101637_N02.12', 'S2B_OPER_MSI_L2A_DS_SGS__20190529T143958_S20190529T101637_N02.12', 'S2B_OPER_MSI_L2A_DS_MPS__20190601T135040_S20190601T102031_N02.12', 'S2B_OPER_MSI_L2A_DS_MPS__20190601T135040_S20190601T102031_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190603T130327_S20190603T101642_N02.12', 'S2A_OPER_MSI_L2A_DS_SGS__20190603T130327_S20190603T101642_N02.12', 'S2A_OPER_MSI_L2A_DS_MPS__20190606T134450_S20190606T102358_N02.12', 'S2A_OPER_MSI_L2A_DS_MPS__20190606T134450_S20190606T102358_N02.12'], dtype='<U64') - s2:water_percentage(time)object0.000192 0 0 ... 0.018796 0.058846
array([0.000192, 0, 0, 0.000484, 1.017965, 1.816523, 1.899341, 1.497153, 6e-05, 0.009848, 2.785423, 0.651507, 2.181987, 0.778276, 2.447255, 1.235006, 1.828879, 0.903938, 0.837586, 0.791285, 0.853327, 1.730886, 0.65733, 0.514093, 0.293363, 1.636728, 0.637001, 1.1716, 0.513652, 0, 0.164873, 0.401024, 0.050523, 0, 0.173052, 0.329163, 0.129146, 0.897091, 0.259702, 0.98375, 0.334246, 0.448729, 0.044065, 0.307843, 0.08656, 0.088224, 0.652947, 0.242375, 0.869662, 0.638963, 0.069514, 0, 0.29537, 0.913488, 0.106748, 0.004177, 0.004908, 0.012429, 0.20058, 0.003194, 0.004638, 0.362816, 0.92161, 0.772722, 0.994909, 0.133682, 0.15932, 0.379414, 0.002223, 0.218968, 0.344684, 0.009376, 0.006447, 0.742066, 0.565763, 0.174961, 0.027206, 0.282649, 0.011158, 0.13001, 0.128264, 0, 0, 0.030364, 0.298453, 0.344691, 0.001257, 0.271203, 0.003447, 1.050406, 0.597798, 0, 0, 0.00147, 0.001433, 0.916469, 0.398205, 1.264722, 0.621998, 0.018796, 0.058846], dtype=object) - s2:product_type()<U7'S2MSI2A'
array('S2MSI2A', dtype='<U7') - created(time)<U24'2022-11-08T12:14:57.099Z' ... '...
array(['2022-11-08T12:14:57.099Z', '2022-11-08T12:07:15.671Z', '2022-11-08T11:58:42.239Z', '2022-11-08T11:52:31.873Z', '2022-11-08T11:58:53.378Z', '2022-11-08T11:52:21.920Z', '2022-11-08T11:58:53.183Z', '2022-11-08T12:05:25.354Z', '2022-11-08T11:58:38.817Z', '2022-11-08T12:07:19.166Z', '2022-11-08T11:58:38.972Z', '2022-11-08T11:49:31.028Z', '2022-11-08T12:00:56.277Z', '2022-11-03T09:55:31.023Z', '2022-11-03T11:08:00.382Z', '2022-11-08T12:07:18.675Z', '2022-11-08T12:00:33.368Z', '2022-11-08T12:07:21.011Z', '2022-11-08T12:05:37.791Z', '2022-11-03T11:11:05.412Z', '2022-11-03T10:10:43.801Z', '2022-11-08T11:58:38.091Z', '2022-11-03T10:23:18.376Z', '2022-11-08T11:58:53.430Z', '2022-11-08T12:05:32.318Z', '2022-11-08T11:59:26.092Z', '2022-11-08T11:51:02.353Z', '2022-11-08T11:50:46.933Z', '2022-11-08T12:15:05.389Z', '2022-11-08T11:58:46.175Z', '2022-11-08T12:05:32.031Z', '2022-11-08T11:58:42.836Z', '2022-11-08T12:06:07.127Z', '2022-11-08T12:16:43.099Z', '2022-11-08T12:06:06.731Z', '2022-11-08T12:16:42.257Z', '2022-11-08T11:49:40.179Z', '2022-11-08T12:01:02.143Z', '2022-11-08T11:49:37.014Z', '2022-11-08T12:01:02.928Z', ... '2022-11-08T11:52:40.408Z', '2022-11-08T11:49:50.068Z', '2022-11-08T12:02:19.750Z', '2022-11-08T12:07:28.698Z', '2022-11-08T12:00:10.208Z', '2022-11-08T12:15:16.747Z', '2022-11-03T10:13:09.527Z', '2022-11-08T12:15:12.852Z', '2022-11-03T10:13:06.703Z', '2022-11-08T11:59:21.436Z', '2022-11-08T11:50:19.185Z', '2022-11-08T12:15:16.737Z', '2022-11-08T11:51:16.405Z', '2022-11-08T11:58:50.572Z', '2022-11-08T11:50:40.069Z', '2022-11-03T11:06:08.579Z', '2022-11-08T11:51:46.114Z', '2022-11-08T12:00:09.471Z', '2022-11-08T11:51:45.682Z', '2022-11-08T12:02:23.263Z', '2022-11-08T12:06:47.113Z', '2022-11-08T12:02:23.988Z', '2022-11-08T11:52:02.349Z', '2022-11-08T11:58:48.381Z', '2022-11-08T11:51:45.394Z', '2022-11-08T11:58:51.691Z', '2022-11-08T11:51:14.010Z', '2022-11-08T12:15:17.288Z', '2022-11-08T11:50:08.078Z', '2022-11-08T12:16:04.090Z', '2022-11-08T11:50:06.979Z', '2022-11-08T12:16:04.002Z', '2022-11-08T11:50:39.650Z', '2022-11-08T12:00:15.273Z', '2022-11-03T10:26:49.137Z', '2022-11-08T12:16:10.906Z', '2022-11-08T11:50:14.408Z', '2022-11-08T12:01:59.464Z', '2022-11-08T11:51:35.276Z'], dtype='<U24') - mgrs:latitude_band()<U1'T'
array('T', dtype='<U1') - s2:granule_id(time)<U62'S2B_OPER_MSI_L2A_TL_SGS__201902...
array(['S2B_OPER_MSI_L2A_TL_SGS__20190201T125655_A009958_T32TPT_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190201T125655_A009958_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190203T124425_A018895_T32TPT_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190203T124425_A018895_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190206T132004_A018938_T32TPT_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190206T132004_A018938_T32TPS_N02.11', 'S2B_OPER_MSI_L2A_TL_MPS__20190208T132121_A010058_T32TPT_N02.11', 'S2B_OPER_MSI_L2A_TL_MPS__20190208T132121_A010058_T32TPS_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190211T143627_A010101_T32TPT_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190211T143627_A010101_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190213T162253_A019038_T32TPT_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190213T162253_A019038_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190216T130428_A019081_T32TPT_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190216T130428_A019081_T32TPS_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190218T161620_A010201_T32TPT_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190218T161620_A010201_T32TPS_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190221T162447_A010244_T32TPT_N02.11', 'S2B_OPER_MSI_L2A_TL_SGS__20190221T162447_A010244_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_MPS__20190223T134548_A019181_T32TPS_N02.11', 'S2A_OPER_MSI_L2A_TL_SGS__20190226T143434_A019224_T32TPT_N02.11', ... 'S2B_OPER_MSI_L2A_TL_MPS__20190512T134103_A011388_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_MPS__20190514T134657_A020325_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_MPS__20190514T134657_A020325_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190517T131216_A020368_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190517T131216_A020368_T32TPS_N02.12', 'S2B_OPER_MSI_L2A_TL_MPS__20190519T132053_A011488_T32TPT_N02.12', 'S2B_OPER_MSI_L2A_TL_MPS__20190519T132053_A011488_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190524T130304_A020468_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190524T130304_A020468_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190527T145156_A020511_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190527T145156_A020511_T32TPS_N02.12', 'S2B_OPER_MSI_L2A_TL_SGS__20190529T143958_A011631_T32TPT_N02.12', 'S2B_OPER_MSI_L2A_TL_SGS__20190529T143958_A011631_T32TPS_N02.12', 'S2B_OPER_MSI_L2A_TL_MPS__20190601T135040_A011674_T32TPT_N02.12', 'S2B_OPER_MSI_L2A_TL_MPS__20190601T135040_A011674_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190603T130327_A020611_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_SGS__20190603T130327_A020611_T32TPS_N02.12', 'S2A_OPER_MSI_L2A_TL_MPS__20190606T134450_A020654_T32TPT_N02.12', 'S2A_OPER_MSI_L2A_TL_MPS__20190606T134450_A020654_T32TPS_N02.12'], dtype='<U62') - s2:sequence(time)<U1'0' '0' '0' '0' ... '0' '0' '0' '0'
array(['0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0'], dtype='<U1') - s2:processing_baseline(time)<U5'02.11' '02.11' ... '02.12' '02.12'
array(['02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.11', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12', '02.12'], dtype='<U5') - proj:epsg()int6432632
array(32632)
- gsd()objectNone
array(None, dtype=object)
- raster:bands()object{'nodata': 0, 'data_type': 'uint...
array({'nodata': 0, 'data_type': 'uint8', 'spatial_resolution': 20}, dtype=object) - title()<U30'Scene classification map (SCL)'
array('Scene classification map (SCL)', dtype='<U30') - common_name()objectNone
array(None, dtype=object)
- center_wavelength()objectNone
array(None, dtype=object)
- full_width_half_max()objectNone
array(None, dtype=object)
- epsg()int6432632
array(32632)
- spatial_ref()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 32N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",9],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32632"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 32N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 9.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 32N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",9],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32632"]]
- GeoTransform :
- 654290.0 20.0 0.0 5202350.0 0.0 -20.0
array(0)
- timePandasIndex
PandasIndex(DatetimeIndex(['2019-02-01 10:27:41.665000', '2019-02-01 10:27:55.803000', '2019-02-03 10:17:41.721000', '2019-02-03 10:17:56.196000', '2019-02-06 10:27:38.251000', '2019-02-06 10:27:52.378000', '2019-02-08 10:17:45.015000', '2019-02-08 10:17:59.486000', '2019-02-11 10:27:41.425000', '2019-02-11 10:27:55.562000', ... '2019-05-27 10:27:44.339000', '2019-05-27 10:27:58.464000', '2019-05-29 10:17:53.232000', '2019-05-29 10:18:07.701000', '2019-06-01 10:27:49.632000', '2019-06-01 10:28:03.768000', '2019-06-03 10:17:47.026000', '2019-06-03 10:18:01.498000', '2019-06-06 10:27:43.405000', '2019-06-06 10:27:57.521000'], dtype='datetime64[ns]', name='time', length=101, freq=None))
clipped_date = snowmap_clipped.groupby(snowmap_clipped.time.dt.floor('D')).max(skipna=True)
as the data has been aggregated to daily values, we need to rename the floor method to something more meaningfull as date.
clipped_date = clipped_date.rename({'floor': 'date'})
clipped_date = clipped_date.persist()
Visualize data#
We will use the hvplot library to visualize the data. The hvplot library is a library that allows to visualize data in xarray datasets. It is based on the holoviews library, which is a library that allows to visualize multidimensional data. As we are going to visualize the data on a map, we need to specify the coordinate reference system of the data. The data is in the UTM32N coordinate reference system (EPSG:32632). This will allow the library to project the data on a map. More info on the hvplot library can be found here: https://hvplot.holoviz.org/
clipped_date.hvplot.image(
x='x',
y='y',
groupby='date',
crs=pyproj.CRS.from_epsg(32632),
cmap='Pastel2',
clim=(-1, 2),
frame_width=500,
frame_height=500,
title='Snowmap',
geo=True, tiles='OSM')